CVPR2021最新信息及已接收论文/代码(持续更新)

官网链接：http://cvpr2021.thecvf.com
开会时间：2021年6月19日-6月25日
论文接收公布时间：2021年2月28日

接收论文IDs：

• CVPR 2021 接收论文列表！27%接受率！

:exclamation::exclamation::exclamation:🌟🌟🌟 CVPR 2021 收录论文已全部公布，下载可在【我爱计算机视觉】后台回复“CVPR2021”，即可收到。共计 1660 篇。

:exclamation::exclamation::exclamation:🌟🌟🌟 全部论文已粗略分类完毕，请查阅。

:exclamation::exclamation::exclamation:注：后续论文的细致分类汇总将发布在公众号【OpenCV中文网】，敬请关注。

历年综述论文分类汇总戳这里↘️CV-Surveys施工中~~~~~~~~~~

2022 年论文分类汇总戳这里

↘️CVPR-2022-Papers ↘️WACV-2022-Papers

2021年论文分类汇总戳这里

↘️ICCV-2021-Papers ↘️CVPR-2021-Papers

2020 年论文分类汇总戳这里

↘️CVPR-2020-Papers ↘️ECCV-2020-Papers

目录

74.Place Recognition(位置识别)

• SOE-Net: A Self-Attention and Orientation Encoding Network for Point Cloud Based Place Recognition
  :open_mouth:oral:star:code

73.Object Re-identification(物体重识别)

• Refining Pseudo Labels with Clustering Consensus over Generations for Unsupervised Object Re-identification

72.Gaze Estimation(视线估计)

• Weakly-Supervised Physically Unconstrained Gaze Estimation
  :open_mouth:oral:star:code
• Gaze 目标检测
  • Dual Attention Guided Gaze Target Detection in the Wild
    :star:code

71.Image-to-Image Translation(图像到图像翻译)

• High-Resolution Photorealistic Image Translation in Real-Time: A Laplacian Pyramid Translation Network
  :star:code
• CoCosNet v2: Full-Resolution Correspondence Learning for Image Translation
  :open_mouth:oral:house:project
  解读：CoCosNet v2解锁“高配版”图像翻译
• Smoothing the Disentangled Latent Style Space for Unsupervised Image-to-Image Translation
• Saliency-Guided Image Translation
• Not Just Compete, but Collaborate: Local Image-to-Image Translation via Cooperative Mask Prediction
• Unpaired Image-to-Image Translation via Latent Energy Transport
  :star:code
• 图像翻译
  • Unbalanced Feature Transport for Exemplar-Based Image Translation
  • The Spatially-Correlative Loss for Various Image Translation Tasks
    :star:code:house:project:tv:video

70.NLP(自然语言处理)

• Learning Graphs for Knowledge Transfer With Limited Labels
  :star:code:house:project

69.Transfer learning(迁移学习)

• 域迁移
  • Visualizing Adapted Knowledge in Domain Transfer
    :star:code

68.Crowd Counting(计数)

• Learning To Count Everything
  :star:code

67.Defect Detection(缺陷检测)

• CutPaste: Self-Supervised Learning for Anomaly Detection and Localization

66.Optical Flow Estimation(光流估计)

• UPFlow:Upsampling Pyramid for Unsupervised Optical Flow Learning
  粗解：8
• Learning Optical Flow from a Few Matches
  :star:code
• Learning optical flow from still images
  :star:code:house:project
• AutoFlow: Learning a Better Training Set for Optical Flow
  :house:project
  AutoFlow ：CVPR 2021 Oral ,作者发明了一种专为光流算法训练而设计的数据渲染方法，所训练得到的PWC-Net 与 RAFT光流算法达到了SOTA,代码和数据将开源。
• UPFlow: Upsampling Pyramid for Unsupervised Optical Flow Learning
  :star:code

65.Style Transfer(风格迁移)

• Rethinking Style Transfer: From Pixels to Parameterized Brushstrokes
  :star:code
• ArtFlow: Unbiased Image Style Transfer via Reversible Neural Flows
  :star:code
• Lipstick ain't enough: Beyond Color Matching for In-the-Wild Makeup Transfer
  :star:code
• Rethinking and Improving the Robustness of Image Style Transfer
  :open_mouth:oral
  解读：CVPR2021 最佳论文候选—提高图像风格迁移的鲁棒性
• Drafting and Revision: Laplacian Pyramid Network for Fast High-Quality Artistic Style Transfer
  :star:code
• Style-Aware Normalized Loss for Improving Arbitrary Style Transfer
  :open_mouth:oral
• In the Light of Feature Distributions: Moment Matching for Neural Style Transfer
  :star:code:house:project
• ArtCoder: An End-to-End Method for Generating Scanning-Robust Stylized QR Codes
• Adaptive Convolutions for Structure-Aware Style Transfer
• Learning To Warp for Style Transfer
  :star:code
• Single-Shot Freestyle Dance Reenactment
• CT-Net: Complementary Transfering Network for Garment Transfer With Arbitrary Geometric Changes
• DualAST: Dual Style-Learning Networks for Artistic Style Transfer
  :star:code
• What Can Style Transfer and Paintings Do For Model Robustness?
  :star:code
• 运动迁移
  • Autoregressive Stylized Motion Synthesis with Generative Flow

64.Speech processing(语音处理)

• Can audio-visual integration strengthen robustness under multimodal attacks?
  :star:code
• Robust Audio-Visual Instance Discrimination
• 立体音频生成
  • Visually Informed Binaural Audio Generation without Binaural Audios
    :star:code:house:project:tv:video
• 视听分离
  • Looking into Your Speech: Learning Cross-modal Affinity for Audio-visual Speech Separation
    :house:project:tv:video
  • Cyclic Co-Learning of Sounding Object Visual Grounding and Sound Separation
    :star:code
  • VisualVoice: Audio-Visual Speech Separation With Cross-Modal Consistency
    :star:code:house:project
• 声音-视频解析
  • Exploring Heterogeneous Clues for Weakly-Supervised Audio-Visual Video Parsing
• A-V
  • Positive Sample Propagation Along the Audio-Visual Event Line
    :star:code
• 语音人脸关联
  • Seeking the Shape of Sound: An Adaptive Framework for Learning Voice-Face Association

63.Image Processing(图像处理)

• 图像信号处理
  • Invertible Image Signal Processing
    :star:code:house:project
• 光谱重建
  • Tuning IR-cut Filter for Illumination-aware Spectral Reconstruction from RGB
    :open_mouth:oral

62.Free-Hand Sketches(手绘草图识别)

• Cloud2Curve: Generation and Vectorization of Parametric Sketches

61.算法

• 因果推理算法
  • ACRE: Abstract Causal REasoning Beyond Covariation
    :star:code:house:project
• 抽象时空推理算法
  • Abstract Spatial-Temporal Reasoning via Probabilistic Abduction and Execution
    :star:code:house:project

60. SLAM/AR/机器人

• Tangent Space Backpropagation for 3D Transformation Groups
  :star:code
• 视觉里程计
  • Generalizing to the Open World: Deep Visual Odometry with Online Adaptation
• 机器人
  • Visual Room Rearrangement
    :open_mouth:oral:house:project:tv:video
  • GATSBI: Generative Agent-centric Spatio-temporal Object Interaction
    :open_mouth:oral:star:code:tv:video
  • DexYCB: A Benchmark for Capturing Hand Grasping of Objects
    :star:code:house:project:tv:video
  • ContactOpt: Optimizing Contact to Improve Grasps
    :star:code
    机器人手抓取
  • ManipulaTHOR: A Framework for Visual Object Manipulation
    :open_mouth:oral:star:code:house:project:tv:video
  • 视觉导航
    • Pushing it out of the Way: Interactive Visual Navigation
      :house:project:tv:video
    • Differentiable SLAM-net: Learning Particle SLAM for Visual Navigation
      :house:project:tv:video
• AR
  • Stay Positive: Non-Negative Image Synthesis for Augmented Reality
    :open_mouth:oral:star:code
  • HDR Environment Map Estimation for Real-Time Augmented Reality:tv:video
  • NeuralHumanFVV: Real-Time Neural Volumetric Human Performance Rendering Using RGB Cameras
  • 虚拟试穿
    • VITON-HD: High-Resolution Virtual Try-On via Misalignment-Aware Normalization
    • Self-Supervised Collision Handling via Generative 3D Garment Models for Virtual Try-On
      :house:project:tv:video
    • Toward Accurate and Realistic Outfits Visualization with Attention to Details
    • ANR: Articulated Neural Rendering for Virtual Avatars
      :house:project
    • Parser-Free Virtual Try-On via Distilling Appearance Flows
      :star:code

59.Capsule Network(胶囊网络)(深度学习模型)

• Dynamic Slimmable Network
  :open_mouth:oral:star:code
• Towards Evaluating and Training Verifiably Robust Neural Networks
  :open_mouth:oral:star:code
• Activate or Not: Learning Customized Activation
  :star:code
  粗解：4
  解读：CVPR 2021 | 自适应激活函数ACON: 统一ReLU和Swish的新范式
• DISCO: Dynamic and Invariant Sensitive Channel Obfuscation for Deep Neural Networks
  :star:code
• Capsule Network(胶囊网络)
  • Capsule Network Is Not More Robust Than Convolutional Network

58.Metric Learning(度量学习/相似度学习)

• Dynamic Metric Learning: Towards a Scalable Metric Space to Accommodate Multiple Semantic Scales
  :star:code
• Embedding Transfer with Label Relaxation for Improved Metric Learning
• Noise-resistant Deep Metric Learning with Ranking-based Instance Selection
  :star:code
• Unsupervised Hyperbolic Metric Learning
• Deep Compositional Metric Learning
  :star:code
• SLADE: A Self-Training Framework for Distance Metric Learning
• Asymmetric Metric Learning for Knowledge Transfer
  :star:code
• Relative Order Analysis and Optimization for Unsupervised Deep Metric Learning

57.Sign Language Recognition(手语识别)

• Skeleton Based Sign Language Recognition Using Whole-body Keypoints
  :star:code
• Read and Attend: Temporal Localisation in Sign Language Videos
  :house:project
• Fingerspelling Detection in American Sign Language
• 手语翻译
  • Improving Sign Language Translation with Monolingual Data by Sign Back-Translation
    :sunflower:dataset

56.Computational Photography(光学、几何、光场成像、计算摄影)

• Deep Gaussian Scale Mixture Prior for Spectral Compressive Imaging
  :star:code:house:project
• Mask-ToF: Learning Microlens Masks for Flying Pixel Correction in Time-of-Flight Imaging
  :house:project
• Passive Inter-Photon Imaging
  :open_mouth:oral
• Shape and Material Capture at Home
  :star:code:house:project
• Event-based Synthetic Aperture Imaging with a Hybrid Network
  分享会
• High-Speed Image Reconstruction Through Short-Term Plasticity for Spiking Cameras
• Leveraging the Availability of Two Cameras for Illuminant Estimation
• 相机姿势
  • Fusing the Old with the New: Learning Relative Camera Pose with Geometry-Guided Uncertainty
    :open_mouth:oral
  • Learning Neural Representation of Camera Pose with Matrix Representation of Pose Shift via View Synthesis
    :star:code
  • Uncertainty-Aware Camera Pose Estimation From Points and Lines
    :star:code:house:project
  • Neural Reprojection Error: Merging Feature Learning and Camera Pose Estimation
    :star:code:house:project
  • Wide-Baseline Relative Camera Pose Estimation with Directional Learning
  • Camera Pose Matters: Improving Depth Prediction by Mitigating Pose Distribution Bias
    :open_mouth:oral
• 室内照明估计
  • Indoor Lighting Estimation Using an Event Camera
• Phase Retrieval相位恢复算法
  • Physics-Based Iterative Projection Complex Neural Network for Phase Retrieval in Lensless Microscopy Imaging

55.Graph Matching(图匹配)

• Deep Graph Matching under Quadratic Constraint
  :star:code

54.Emotion Perception(情绪感知/情感预测)

• Affect2MM: Affective Analysis of Multimedia Content Using Emotion Causality
  :house:project
• Human Multimodal Emotion Recognition(人类多模态情感识别)
  • Progressive Modality Reinforcement for Human Multimodal Emotion Recognition From Unaligned Multimodal Sequences

53.Dataset(数据集)

• Conceptual 12M: Pushing Web-Scale Image-Text Pre-Training To Recognize Long-Tail Visual Concepts
  :sunflower:dataset
• Sewer-ML: A Multi-Label Sewer Defect Classification Dataset and Benchmark
  :house:project
• Benchmarking Representation Learning for Natural World Image Collections
  :sunflower:dataset
• SAIL-VOS 3D: A Synthetic Dataset and Baselines for Object Detection and 3D Mesh Reconstruction from Video Data
  :open_mouth:oral:sunflower:dataset
• Fashion IQ: A New Dataset Towards Retrieving Images by Natural Language Feedback
  :sunflower:dataset
• Towards Semantic Segmentation of Urban-Scale 3D Point Clouds: A Dataset, Benchmarks and Challenges
  :sunflower:dataset:tv:video
  
• 人脸图像修饰数据集
• PPR10K: A Large-Scale Portrait Photo Retouching Dataset with Human-Region Mask and Group-Level Consistency
  :star:code
• 室外场景
  • OpenRooms: An Open Framework for Photorealistic Indoor Scene Datasets
    :open_mouth:oral:sunflower:dataset:house:project
• 视觉艺术
  • ArtEmis: Affective Language for Visual Art
    :house:project主页中包含全部：数据集、代码、视频等
• UGC 视频质量评估
  • Rich Features for Perceptual Quality Assessment of UGC Videos
    :sunflower:dataset
• 室内定位数据集
  • Large-Scale Localization Datasets in Crowded Indoor Spaces
    :sunflower:dataset
  • Zillow Indoor Dataset: Annotated Floor Plans With 360deg Panoramas and 3D Room Layouts
• 数据集(人类意图研究)
  • Intentonomy: A Dataset and Study Towards Human Intent Understanding
    :open_mouth:oral:star:code
• 人脸识别数据集
  • Virtual Fully-Connected Layer: Training a Large-Scale Face Recognition Dataset With Limited Computational Resources
    :star:code
• 视觉属性预测数据集
  • Learning To Predict Visual Attributes in the Wild
    :sunflower:dataset
• 数据集(Object-Centric Videos)
  • Objectron: A Large Scale Dataset of Object-Centric Videos in the Wild With Pose Annotations
    :sunflower:dataset
• 视频场景解析
  • VSPW: A Large-scale Dataset for Video Scene Parsing in the Wild
    :sunflower:dataset:house:project
• 数据集（手语）
  • How2Sign: A Large-Scale Multimodal Dataset for Continuous American Sign Language
    :sunflower:dataset

52. Image Generation/Synthesis(图像生成)

• Spatially-Adaptive Pixelwise Networks for Fast Image Translation
  :house:project
  采用超网络和隐式函数，极快的图像到图像翻译速度（比基线快18倍）
• Image Generators with Conditionally-Independent Pixel Synthesis
  :open_mouth:oral:star:code

• Im2Vec: Synthesizing Vector Graphics without Vector Supervision
  :open_mouth:oral:star:code:house:project
• Context-Aware Layout to Image Generation with Enhanced Object Appearance
  :star:code
• Adversarial Generation of Continuous Images
  :star:code
• StEP: Style-based Encoder Pre-training for Multi-modal Image Synthesis
• IMAGINE: Image Synthesis by Image-Guided Model Inversion
• SSN: Soft Shadow Network for Image Compositing
• Mask-Embedded Discriminator With Region-Based Semantic Regularization for Semi-Supervised Class-Conditional Image Synthesis
• Learning Semantic Person Image Generation by Region-Adaptive Normalization
  :star:code
• MUST-GAN: Multi-Level Statistics Transfer for Self-Driven Person Image Generation
• Combining Semantic Guidance and Deep Reinforcement Learning for Generating Human Level Paintings
  :star:code
• Diverse Semantic Image Synthesis via Probability Distribution Modeling
  :star:code
• Mol2Image: Improved Conditional Flow Models for Molecule to Image Synthesis

51.Contrastive Learning(对比学习)

• AdCo: Adversarial Contrast for Efficient Learning of Unsupervised Representations from Self-Trained Negative Adversaries
  :star:code
  解读:CVPR 2021接收论文：AdCo基于对抗的对比学习
• LAFEAT: Piercing Through Adversarial Defenses with Latent Features
  :open_mouth:oral:star:code
• Distilling Audio-Visual Knowledge by Compositional Contrastive Learning
  :star:code
• Mining Better Samples for Contrastive Learning of Temporal Correspondence
• Jo-SRC: A Contrastive Approach for Combating Noisy Labels
  :star:code
• Neighborhood Contrastive Learning for Novel Class Discovery

50.OCR

• Fourier Contour Embedding for Arbitrary-Shaped Text Detection
• Implicit Feature Alignment: Learn to Convert Text Recognizer to Text Spotter
• Sequence-to-Sequence Contrastive Learning for Text Recognition
• A Multiplexed Network for End-to-End, Multilingual OCR
• TAP: Text-Aware Pre-Training for Text-VQA and Text-Caption
• 场景文本检测
  • What If We Only Use Real Datasets for Scene Text Recognition? Toward Scene Text Recognition With Fewer Labels
    :star:code
  • Read Like Humans: Autonomous, Bidirectional and Iterative Language Modeling for Scene Text Recognition
    :open_mouth:oral:star:code
  • MOST: A Multi-Oriented Scene Text Detector with Localization Refinement
  • Scene Text Retrieval via Joint Text Detection and Similarity Learning
    :star:code
  • TextOCR: Towards large-scale end-to-end reasoning for arbitrary-shaped scene text
    :house:project
  • Progressive Contour Regression for Arbitrary-Shape Scene Text Detection
    :star:code
  • Dictionary-guided Scene Text Recognition
    :star:code
  • Primitive Representation Learning for Scene Text Recognition
• 手写文本识别
  • MetaHTR: Towards Writer-Adaptive Handwritten Text Recognition
• 文本分割
  • Rethinking Text Segmentation: A Novel Dataset and a Text-Specific Refinement Approach
    :star:code
• 视频文本检测
  • Semantic-Aware Video Text Detection
• 文本检测
  • Self-Attention Based Text Knowledge Mining for Text Detection
    :star:code

49.Adversarial Learning(对抗学习)

• Simulating Unknown Target Models for Query-Efficient Black-box Attacks
  :star:code
  黑盒对抗攻击
• Delving into Data: Effectively Substitute Training for Black-box Attack
  基于高效训练替代模型的黑盒攻击方法
  解读：8
• LiBRe: A Practical Bayesian Approach to Adversarial Detection
  :star:code

• Invisible Perturbations: Physical Adversarial Examples Exploiting the Rolling Shutter Effect
• Enhancing the Transferability of Adversarial Attacks Through Variance Tuning
  :star:code
• Natural Adversarial Examples
  :star:code
• SurFree: A Fast Surrogate-Free Black-Box Attack
  :star:code
• Regularizing Neural Networks via Adversarial Model Perturbation
  :star:code
• Adversarial Imaging Pipelines
• MAZE: Data-Free Model Stealing Attack Using Zeroth-Order Gradient Estimation
• Universal Spectral Adversarial Attacks for Deformable Shapes
• Adversarial Robustness Across Representation Spaces
  :star:code
• Protecting Intellectual Property of Generative Adversarial Networks From Ambiguity Attacks
  :star:code
• Dual Attention Suppression Attack: Generate Adversarial Camouflage in Physical World
  :open_mouth:oral:star:code
• Learning Compositional Representation for 4D Captures with Neural ODE
• 对抗攻击
  • Adversarial Laser Beam: Effective Physical-World Attack to DNNs in a Blink

48.Image Representation(图像表示)

• Learning Continuous Image Representation with Local Implicit Image Function
  :open_mouth:oral:star:code:house:project:tv:video

47.Vision-Language(视觉语言)

• Structured Scene Memory for Vision-Language Navigation
  :star:code

• Kaleido-BERT: Vision-Language Pre-training on Fashion Domain
  
• Seeing Out of tHe bOx: End-to-End Pre-training for Vision-Language Representation Learning
  :star:code
• UC2: Universal Cross-Lingual Cross-Modal Vision-and-Language Pre-Training
• VinVL: Revisiting Visual Representations in Vision-Language Models
  :star:code
• Connecting What To Say With Where To Look by Modeling Human Attention Traces
  :star:code:house:project
• Adaptive Cross-Modal Prototypes for Cross-Domain Visual-Language Retrieval
• VLN BERT: A Recurrent Vision-and-Language BERT for Navigation
  :open_mouth:oral:star:code
• Transitional Adaptation of Pretrained Models for Visual Storytelling
• Learning Better Visual Dialog Agents With Pretrained Visual-Linguistic Representation
  :star:code
• Causal Attention for Vision-Language Tasks
  :star:code

46.Human-Object Interaction(人物交互)

• Learning Asynchronous and Sparse Human-Object Interaction in Videos
• QPIC: Query-Based Pairwise Human-Object Interaction Detection with Image-Wide Contextual Information
  :star:code
• Reformulating HOI Detection as Adaptive Set Prediction
  :star:code

• Detecting Human-Object Interaction via Fabricated Compositional Learning
  :star:code
• Affordance Transfer Learning for Human-Object Interaction Detection
  :star:code
• Glance and Gaze: Inferring Action-aware Points for One-Stage Human-Object Interaction Detection
  :star:code
• Hierarchical Video Prediction Using Relational Layouts for Human-Object Interactions

45.Camera Localization(相机定位)

• Robust Neural Routing Through Space Partitions for Camera Relocalization in Dynamic Indoor Environments
  :open_mouth:oral
• Back to the Feature: Learning Robust Camera Localization from Pixels to Pose
  :star:code
• Learning Camera Localization via Dense Scene Matching
  :star:code
• Privacy Preserving Localization and Mapping From Uncalibrated Cameras

• 视觉定位
  • VS-Net: Voting with Segmentation for Visual Localization
    :star:code:house:project:tv:video

44. Image/video Captioning(图像/视频字幕)

• Scan2Cap: Context-aware Dense Captioning in RGB-D Scans
  :star:code:house:project:tv:video
• VX2TEXT: End-to-End Learning of Video-Based Text Generation From Multimodal Inputs
  视频字幕、视频问答和视频对话任务的多模式框架
• Open-book Video Captioning with Retrieve-Copy-Generate Network

• 图像字幕
  • Human-like Controllable Image Captioning with Verb-specific Semantic Roles
    :star:code
  • Towards Accurate Text-based Image Captioning with Content Diversity Exploration
    :star:code
  • Image Change Captioning by Learning From an Auxiliary Task
  • FAIEr: Fidelity and Adequacy Ensured Image Caption Evaluation
    :star:code
  • Towards Bridging Event Captioner and Sentence Localizer for Weakly Supervised Dense Event Captioning
  • Improving OCR-Based Image Captioning by Incorporating Geometrical Relationship

43.Active Learning(主动学习)

• Vab-AL: Incorporating Class Imbalance and Difficulty with Variational Bayes for Active Learning

• Task-Aware Variational Adversarial Active Learning
  :star:code

42.Scene Flow Estimation(场景流估计)

• 场景流估计
  • Self-Supervised Multi-Frame Monocular Scene Flow
    :star:code
  • HCRF-Flow: Scene Flow from Point Clouds with Continuous High-order CRFs and Position-aware Flow Embedding
  • Self-Point-Flow: Self-Supervised Scene Flow Estimation from Point Clouds with Optimal Transport and Random Walk
    :open_mouth:oral
  • FlowStep3D: Model Unrolling for Self-Supervised Scene Flow Estimation
    :star:code
  • RAFT-3D: Scene Flow Using Rigid-Motion Embeddings

41. Representation Learning(表示学习（图像+字幕）)

• VirTex: Learning Visual Representations from Textual Annotations
  :star:code
• Exploring Simple Siamese Representation Learning
  :open_mouth:oral:star:code
• Representation Learning via Global Temporal Alignment and Cycle-Consistency
  :star:code

• SelfDoc: Self-Supervised Document Representation Learning
• CausalVAE: Disentangled Representation Learning via Neural Structural Causal Models
• Unsupervised Hyperbolic Representation Learning via Message Passing Auto-Encoders
  :star:code
• Boosting Video Representation Learning With Multi-Faceted Integration

40.Superpixel (超像素)

• Learning the Superpixel in a Non-iterative and Lifelong Manner
  :star:code

39.Debiasing(去偏见)

• Fair Attribute Classification through Latent Space De-biasing
  :star:code:house:project
  
• Reducing Domain Gap by Reducing Style Bias
  :star:code

• 偏差矫正
  • EnD: Entangling and Disentangling deep representations for bias correction
    :star:code

38.Class-Incremental learning(类增量学习)

• IIRC: Incremental Implicitly-Refined Classification
  :house:project
  
• Semantic-aware Knowledge Distillation for Few-Shot Class-Incremental Learning
  :star:code
• DER: Dynamically Expandable Representation for Class Incremental Learning
  :star:code
• Distilling Causal Effect of Data in Class-Incremental Learning
  :star:code
• Self-Promoted Prototype Refinement for Few-Shot Class-Incremental Learning

• Adaptive Aggregation Networks for Class-Incremental Learning
  :star:code
• 增量学习
  • Few-Shot Incremental Learning with Continually Evolved Classifiers
  • On Learning the Geodesic Path for Incremental Learning
    :star:code
  • Prototype Augmentation and Self-Supervision for Incremental Learning
    :open_mouth:oral:star:code
  • Incremental Learning via Rate Reduction

37. Continual Learning(持续学习)

• Training Networks in Null Space for Continual Learning
  :open_mouth:oral:star:code

• Efficient Feature Transformations for Discriminative and Generative Continual Learning
• Rainbow Memory: Continual Learning with a Memory of Diverse Samples
• Rectification-based Knowledge Retention for Continual Learning
• Layerwise Optimization by Gradient Decomposition for Continual Learning
• Continual Learning via Bit-Level Information Preserving
  :star:code
• Training Networks in Null Space of Feature Covariance for Continual Learning
  :open_mouth:oral
• ORDisCo: Effective and Efficient Usage of Incremental Unlabeled Data for Semi-Supervised Continual Learning

36.Action Detection and Recognition(动作检测与识别)

• Coarse-Fine Networks for Temporal Activity Detection in Videos
  :star:code
• 3D CNNs with Adaptive Temporal Feature Resolutions
  :star:code:house:project
• Understanding the Robustness of Skeleton-based Action Recognition under Adversarial Attack
  :tv:video
• BASAR:Black-box Attack on Skeletal Action Recognition
  :house:project:tv:video
  解读：对抗攻防新方向：动作识别算法容易被攻击！
• TDN: Temporal Difference Networks for Efficient Action Recognition
  :star:code
• ACTION-Net: Multipath Excitation for Action Recognition
  :star:code
  解读：CVPR 2021 | 用于动作识别，即插即用、混合注意力机制的 ACTION 模块
  解读：CVPR 2021 ｜针对强时序依赖，即插即用、混合注意力机制的 ACTION 模块
• No frame left behind: Full Video Action Recognition

• Recognizing Actions in Videos from Unseen Viewpoints
• Beyond Short Clips: End-to-End Video-Level Learning with Collaborative Memories
• Motion Representations for Articulated Animation
  :star:code:house:project:tv:video
• Home Action Genome: Cooperative Compositional Action Understanding
• Anticipating human actions by correlating past with the future with Jaccard similarity measures
• Graph-Based High-Order Relation Modeling for Long-Term Action Recognition
• Representing Videos As Discriminative Sub-Graphs for Action Recognition
• Three Birds with One Stone: Multi-Task Temporal Action Detection via Recycling Temporal Annotations
• Learning View-Disentangled Human Pose Representation by Contrastive Cross-View Mutual Information Maximization
  :star:code
• Spatio-temporal Contrastive Domain Adaptation for Action Recognition
• Deep Analysis of CNN-Based Spatio-Temporal Representations for Action Recognition
  :star:code
• Semi-Supervised Action Recognition With Temporal Contrastive Learning
  :star:code:house:project:tv:video
• WOAD: Weakly Supervised Online Action Detection in Untrimmed Videos
• BABEL: Bodies, Action and Behavior With English Labels
  :star:code:house:project:tv:video
• 动作定位
  • Few-Shot Transformation of Common Actions into Time and Space
    :star:code
• 时序动作定位
  • Modeling Multi-Label Action Dependencies for Temporal Action Localization
    :open_mouth:oral:star:code
    提出基于注意力的网络架构来学习视频中的动作依赖性，用于解决多标签时间动作定位任务。
  • The Blessings of Unlabeled Background in Untrimmed Videos
    :star:code
  • Temporal Context Aggregation Network for Temporal Action Proposal Refinement
  • Learning Salient Boundary Feature for Anchor-free Temporal Action Localization
    基于显著边界特征学习的无锚框时序动作定位
    解读：10
  • CoLA: Weakly-Supervised Temporal Action Localization with Snippet Contrastive Learning
  • Action Unit Memory Network for Weakly Supervised Temporal Action Localization
  • Actor-Context-Actor Relation Network for Spatio-Temporal Action Localization
    :star:code
  • Uncertainty Guided Collaborative Training for Weakly Supervised Temporal Action Detection
• Video Actor Segmentation
  • Collaborative Spatial-Temporal Modeling for Language-Queried Video Actor Segmentation
• 动作分割
  • Learning To Segment Actions From Visual and Language Instructions via Differentiable Weak Sequence Alignment
  • 时序动作分割
    • Temporal Action Segmentation from Timestamp Supervision
      :star:code
    • Temporally-Weighted Hierarchical Clustering for Unsupervised Action Segmentation
      :star:code
  • 无监督动作分割
    • Action Shuffle Alternating Learning for Unsupervised Action Segmentation
  • 监督动作分割
  • Anchor-Constrained Viterbi for Set-Supervised Action Segmentation
  • 视频动作分割
    • Global2Local: Efficient Structure Search for Video Action Segmentation
      :star:code
      从全局到局部：面向视频动作分割的高效网络结构搜索
      解读：19
• Video Moment Localization(视频时刻定位)
  • Structured Multi-Level Interaction Network for Video Moment Localization via Language Query
• 时空事件定位
  • Multi-Shot Temporal Event Localization: A Benchmark
    :star:code:house:project

35.Image Clustering(图像聚类)

• Improving Unsupervised Image Clustering With Robust Learning
  :star:code
  利用鲁棒学习改进无监督图像聚类技术
  
• Jigsaw Clustering for Unsupervised Visual Representation Learning
  :open_mouth:oral:star:code
• COMPLETER: Incomplete Multi-view Clustering via Contrastive Prediction
  :star:code

34.Image Classification(图像分类)

• Re-labeling ImageNet: from Single to Multi-Labels, from Global to Localized Labels
  :star:code
  
• Differentiable Patch Selection for Image Recognition
  :star:code
• Achieving Robustness in Classification Using Optimal Transport With Hinge Regularization
• Are Labels Always Necessary for Classifier Accuracy Evaluation?

• 细粒度分类
  • Fine-grained Angular Contrastive Learning with Coarse Labels
    :open_mouth:oral
    :star:code
    使用自监督进行 Coarse Labels（粗标签）的细粒度分类方面的工作。粗标签与细粒度标签相比，更容易和更便宜，因为细粒度标签通常需要域专家。
  • Graph-based High-Order Relation Discovery for Fine-grained Recognition
    基于特征间高阶关系挖掘的细粒度识别方法
    解读：20
  • Few-Shot Classification with Feature Map Reconstruction Networks
    :star:code:tv:video
  • A Realistic Evaluation of Semi-Supervised Learning for Fine-Grained Classification
    :open_mouth:oral
  • GLAVNet: Global-Local Audio-Visual Cues for Fine-Grained Material Recognition
  • Learning Deep Classifiers Consistent With Fine-Grained Novelty Detection
  • Your "Flamingo" is My "Bird": Fine-Grained, or Not
    :open_mouth:oral:star:code
  • Discrimination-Aware Mechanism for Fine-Grained Representation Learning
  • Neural Prototype Trees for Interpretable Fine-grained Image Recognition
    :star:code
• 图像分类
  • MetaSAug: Meta Semantic Augmentation for Long-Tailed Visual Recognition
    :star:code
  • PML: Progressive Margin Loss for Long-tailed Age Classification
    
  • Contrastive Learning based Hybrid Networks for Long-Tailed Image Classification
    :house:project
  • Capsule Network is Not More Robust than Convolutional Network
  • Model-Contrastive Federated Learning
    :star:code
  • Towards Good Practices for Efficiently Annotating Large-Scale Image Classification Datasets
    :open_mouth:oral:star:code:house:project
  • Correlated Input-Dependent Label Noise in Large-Scale Image Classification
    :open_mouth:oral:star:code
  • Towards Robust Classification Model by Counterfactual and Invariant Data Generation
    :star:code
  • Dual-Stream Multiple Instance Learning Network for Whole Slide Image Classification With Self-Supervised Contrastive Learning
    :star:code
  • Generative Classifiers as a Basis for Trustworthy Image Classification
    :star:code
  • Synthesize-It-Classifier: Learning a Generative Classifier Through Recurrent Self-Analysis
  • Background Splitting: Finding Rare Classes in a Sea of Background
  • Permuted AdaIN: Reducing the Bias Towards Global Statistics in Image Classification
  • Self-Supervised Wasserstein Pseudo-Labeling for Semi-Supervised Image Classification
  • DAP: Detection-Aware Pre-training with Weak Supervision
• 半监督图像分类
  • SimPLE: Similar Pseudo Label Exploitation for Semi-Supervised Classification
    :star:code
• 视觉识别
  • Fair Feature Distillation for Visual Recognition
  • 长尾视觉识别
    • Distribution Alignment: A Unified Framework for Long-tail Visual Recognition
      :star:code
    • Improving Calibration for Long-Tailed Recognition
      :star:code
    • Adversarial Robustness under Long-Tailed Distribution
      :open_mouth:oral:star:code
    • Disentangling Label Distribution for Long-Tailed Visual Recognition
      :star:code
    • Long-Tailed Multi-Label Visual Recognition by Collaborative Training on Uniform and Re-Balanced Samplings
• 物体分类
  • Object Classification From Randomized EEG Trials
• Nearest Neighbor Matching(最近邻匹配)
  • Nearest Neighbor Matching for Deep Clustering
    :star:code
• OOD检测
  • MOS: Towards Scaling Out-of-distribution Detection for Large Semantic Space
    :open_mouth:oral:star:code
  • MOOD: Multi-level Out-of-distribution Detection
    :star:code
  • Out-of-Distribution Detection Using Union of 1-Dimensional Subspaces
    :star:code

33.6D Pose Estimation(6D位姿估计)

• FFB6D: A Full Flow Bidirectional Fusion Network for 6D Pose Estimation
  :open_mouth:oral:star:code
  
• GDR-Net: Geometry-Guided Direct Regression Network for Monocular 6D Object Pose Estimation
  :star:code
• FS-Net: Fast Shape-based Network for Category-Level 6D Object Pose Estimation with Decoupled Rotation Mechanism
  :open_mouth:oral:star:code
• Wide-Depth-Range 6D Object Pose Estimation in Space
  :star:code
• DSC-PoseNet: Learning 6DoF Object Pose Estimation via Dual-scale Consistency

• Single-view robot pose and joint angle estimation via render & compare
  :open_mouth:oral:star:code:house:project:tv:video
• Keypoint-Graph-Driven Learning Framework for Object Pose Estimation
• StablePose: Learning 6D Object Poses From Geometrically Stable Patches

32.View Synthesis(视图合成)

• ID-Unet: Iterative Soft and Hard Deformation for View Synthesis
  :open_mouth:oral:star:code
• NeX: Real-time View Synthesis with Neural Basis Expansion
  :open_mouth:oral:house:project:tv:video
  利用神经基础扩展的实时视图合成技术
• Layout-Guided Novel View Synthesis from a Single Indoor Panorama
  :star:code
• Stereo Radiance Fields (SRF): Learning View Synthesis for Sparse Views of Novel Scenes
  :house:project
• Stable View Synthesis
  :star:code

• Neural Scene Flow Fields for Space-Time View Synthesis of Dynamic Scenes
  :house:project:tv:video

31.Open-Set Recognition(开放集识别)

• Counterfactual Zero-Shot and Open-Set Visual Recognition
  :star:code
  
• Few-shot Open-set Recognition by Transformation Consistency
  
• Learning Placeholders for Open-Set Recognition
  :open_mouth:oral

30.Neural rendering(神经渲染)

• DeRF: Decomposed Radiance Fields
  :house:project
  
• D-NeRF: Neural Radiance Fields for Dynamic Scenes
  :house:project
  

• Neural Lumigraph Rendering
  :sunflower:dataset:house:project:tv:video
  斯坦福大学
• AutoInt: Automatic Integration for Fast Neural Volume Rendering
  :open_mouth:oral:house:project:tv:video
  斯坦福大学
• pixelNeRF: Neural Radiance Fields from One or Few Images
  :star:code:house:project:tv:video
• IBRNet: Learning Multi-View Image-Based Rendering
  :house:project
  备注：有学者评论pixelNeRF和IBRNet的工作思想相近，但IBRNet似乎更加成熟。
• Neural Body: Implicit Neural Representations with Structured Latent Codes for Novel View Synthesis of Dynamic Humans
  :star:code:house:project:tv:video
  浙大等学者发明的Neural Body算法，输入多角度视频可输出3D人体和新角度视图。
• NeRV: Neural Reflectance and Visibility Fields for Relighting and View Synthesis
  :house:project:tv:video
  在任意照明条件下，根据一组输入图像生成完整的3D场景
• Self-Supervised Visibility Learning for Novel View Synthesis
  :star:code
• STaR: Self-Supervised Tracking and Reconstruction of Rigid Objects in Motion With Neural Rendering
  :star:code:house:project:tv:video
• Pulsar: Efficient Sphere-Based Neural Rendering
• Learning Compositional Radiance Fields of Dynamic Human Heads
  :open_mouth:oral:house:project
• NeRF in the Wild: Neural Radiance Fields for Unconstrained Photo Collections
• Neural Geometric Level of Detail: Real-Time Rendering With Implicit 3D Shapes
  :star:code:house:project
• Space-Time Neural Irradiance Fields for Free-Viewpoint Video
  :house:project:tv:video
• Neural Scene Graphs for Dynamic Scenes
  :open_mouth:oral:house:project:tv:video
• NeuTex: Neural Texture Mapping for Volumetric Neural Rendering

29.Human Pose Estimation(人体姿态估计)

• Camera-Space Hand Mesh Recovery via Semantic Aggregation and Adaptive 2D-1D Registration
  :star:code
  
• Monocular Real-time Full Body Capture with Inter-part Correlations
  :tv:video
  在电影动作特效中，人体运动捕捉是关键技术，高质量的捕捉往往需要特殊设备，而如果能使用普通RGB相机进行运动捕捉，将会使人人都是特效师。该视频来自清华、马普所等单位的学者发表于CVPR2021的论文结果，使用单目RGB相机的动作捕捉。
• Behavior-Driven Synthesis of Human Dynamics
  :star:code:house:project
• Rethinking the Heatmap Regression for Bottom-up Human Pose Estimation
  :star:code
  粗解：2
• Bottom-Up Human Pose Estimation Via Disentangled Keypoint Regression
  :star:code
• SCANimate: Weakly Supervised Learning of Skinned Clothed Avatar Networks
  :open_mouth:oral:house:project
• On Self-Contact and Human Pose
  :house:project
• Lite-HRNet: A Lightweight High-Resolution Network
  :star:code
  解读：Lite-HRNet：轻量级HRNet，FLOPs大幅下降
• Deep Dual Consecutive Network for Human Pose Estimation
  :star:code
• 3D Human Action Representation Learning via Cross-View Consistency Pursuit
  :star:code
• Body Meshes as Points
  :star:code
• Unsupervised Human Pose Estimation through Transforming Shape Templates
  :house:project
• When Human Pose Estimation Meets Robustness: Adversarial Algorithms and Benchmarks
• Learning Dynamics via Graph Neural Networks for Human Pose Estimation and Tracking

• 3D手部重建
  • Model-based 3D Hand Reconstruction via Self-Supervised Learning
    :star:code:tv:video
• 人体运动迁移
  • Few-Shot Human Motion Transfer by Personalized Geometry and Texture Modeling
    :star:code:tv:video
• Human Volumetric Capture
  • POSEFusion: Pose-guided Selective Fusion for Single-view Human Volumetric Capture
    :open_mouth:oral:house:project
  • High-Fidelity Neural Human Motion Transfer from Monocular Video
• 3D人体姿态估计
  • CanonPose: Self-supervised Monocular 3D Human Pose Estimation in the Wild
    :star:code
  • Context Modeling in 3D Human Pose Estimation: A Unified Perspective
  • PCLs: Geometry-aware Neural Reconstruction of 3D Pose with Perspective Crop Layers
    :star:code:tv:video
    通过消除 location-dependent 透视效果来改进3D人体姿势估计技术工作。
    
  • Graph Stacked Hourglass Networks for 3D Human Pose Estimation
  • Human POSEitioning System (HPS): 3D Human Pose Estimation and Self-localization in Large Scenes from Body-Mounted Sensors
    :open_mouth:oral:house:project
  • SimPoE: Simulated Character Control for 3D Human Pose Estimation
    :open_mouth:oral:house:project
  • Reconstructing 3D Human Pose by Watching Humans in the Mirror
    :open_mouth:oral:star:code:house:project
  • Multi-View Multi-Person 3D Pose Estimation with Plane Sweep Stereo
    :star:code
  • PoseAug: A Differentiable Pose Augmentation Framework for 3D Human Pose Estimation
    :open_mouth:oral:star:code
  • AGORA: Avatars in Geography Optimized for Regression Analysis
    :house:project
  • Intelligent Carpet: Inferring 3D Human Pose From Tactile Signals
  • HybrIK: A Hybrid Analytical-Neural Inverse Kinematics Solution for 3D Human Pose and Shape Estimation
    :star:code
  • Neural Descent for Visual 3D Human Pose and Shape
  • Probabilistic 3D Human Shape and Pose Estimation from Multiple Unconstrained Images in the Wild
• 动物姿态估计
  • From Synthetic to Real: Unsupervised Domain Adaptation for Animal Pose Estimation
    :open_mouth:oral:star:code:tv:video
• 3D人体网格配准
  • Locally Aware Piecewise Transformation Fields for 3D Human Mesh Registration
    :star:code:house:project:tv:video
• 多人人体重建
  • Multi-person Implicit Reconstruction from a Single Image
• 3D人体运动
  • We are More than Our Joints: Predicting how 3D Bodies Move
    :house:project:tv:video
    分享会
• 人体运动捕捉
  • Function4D: Real-time Human Volumetric Capture from Very Sparse Consumer RGBD Sensors
    :open_mouth:oral:house:project:tv:video
  • ChallenCap: Monocular 3D Capture of Challenging Human Performances Using Multi-Modal References
• 多人姿态估计
  • FCPose: Fully Convolutional Multi-Person Pose Estimation with Dynamic Instance-Aware Convolutions
    :star:code
    FCPose，无 ROI 和无分组的端到端可训练人体姿势估计器可以达到更好的准确性和速度，在 COCO 数据集上，使用 DLA-34 主干的 FCPose 实时版本比 Mask R-CNN（ResNet-101）快 4.5 倍（41.67FPS vs. 9.26FPS），同时实现了性能的提高。与最近的自上而下和自下而上的方法相比，FCPose 还实现了更好的速度/准确度权衡。
  • Monocular 3D Multi-Person Pose Estimation by Integrating Top-Down and Bottom-Up Networks
    :star:code
• 手-物交互姿态估计
  • Semi-Supervised 3D Hand-Object Poses Estimation with Interactions in Time
    :star:code:house:project:tv:video
• 人体关键点检测
  • Regressive Domain Adaptation for Unsupervised Keypoint Detection
    :star:code
• 3D人体形状
  • LEAP: Learning Articulated Occupancy of People
    :star:code:house:project:tv:video
  • Beyond Static Features for Temporally Consistent 3D Human Pose and Shape From a Video
    :star:code:tv:video
• 人体动画（姿势迁移）
  • Pose-Guided Human Animation From a Single Image in the Wild
• 基于人体感应的3D健身训练自动系统
  • AIFit: Automatic 3D Human-Interpretable Feedback Models for Fitness Training
    :house:project
• 三维人体运动
  • Synthesizing Long-Term 3D Human Motion and Interaction in 3D Scenes
    :star:code:house:project:tv:video
• 三维人体重建
  • StereoPIFu: Depth Aware Clothed Human Digitization via Stereo Vision
    :star:code:house:project
• 手势到手势翻译
  • Model-Aware Gesture-to-Gesture Translation
• 3D人体运动预测
  • Towards Accurate 3D Human Motion Prediction From Incomplete Observations
• 手势识别
  • Body2Hands: Learning To Infer 3D Hands From Conversational Gesture Body Dynamics
    :star:code:house:project:tv:video
• 三维人体网格重建
  • Holistic 3D Human and Scene Mesh Estimation From Single View Images
• 微观手势情感分析
  • iMiGUE: An Identity-Free Video Dataset for Micro-Gesture Understanding and Emotion Analysis
    :star:code
• Dense Human Correspondences
  • HumanGPS: Geodesic PreServing Feature for Dense Human Correspondences
    :star:code:house:project:tv:video

28.Dense prediction(密集预测)

• Densely connected multidilated convolutional networks for dense prediction tasks
  提出的D3Net在语义分割&音乐源分离任务上的表现优于SOTA网络
  
• Dense Contrastive Learning for Self-Supervised Visual Pre-Training
  :open_mouth:oral:star:code

• Propagate Yourself: Exploring Pixel-Level Consistency for Unsupervised Visual Representation Learning
  :star:code
• Densely Connected Multi-Dilated Convolutional Networks for Dense Prediction Tasks
  :star:code

27.Semantic Line Detection(语义线检测)

• Harmonious Semantic Line Detection via Maximal Weight Clique Selection
  :star:code

26.Video Processing(视频相关技术)

• Skip-Convolutions for Efficient Video Processing
• VideoMoCo: Contrastive Video Representation Learning with Temporally Adversarial Examples
  :star:code
• Learning by Aligning Videos in Time
• Hierarchical Motion Understanding via Motion Programs
  :house:project:tv:video
• Stochastic Image-to-Video Synthesis using cINNs
  :star:code:house:project
• Spoken Moments: Learning Joint Audio-Visual Representations from Video Descriptions
  :house:project
• Gradient Forward-Propagation for Large-Scale Temporal Video Modelling
• Learning To Reconstruct High Speed and High Dynamic Range Videos From Events
• 视频摘要
  • Learning Discriminative Prototypes with Dynamic Time Warping
    :star:code
  • Learning Triadic Belief Dynamics in Nonverbal Communication from Videos
    :open_mouth:oral:star:code
• 视频编解码
  • MetaSCI: Scalable and Adaptive Reconstruction for Video Compressive Sensing
    :star:code
  • FVC: A New Framework towards Deep Video Compression in Feature Space
    :open_mouth:oral
  • Memory-Efficient Network for Large-Scale Video Compressive Sensing
    :star:code
  • Deep Learning in Latent Space for Video Prediction and Compression
    :star:code
• 视频插帧
  • FLAVR: Flow-Agnostic Video Representations for Fast Frame Interpolation
    :star:code:house:project
    
  • Deep Animation Video Interpolation in the Wild
    :star:code
  • TimeLens: Event-based Video Frame Interpolation
    :star:code:sunflower:dataset:tv:video
  • Time Lens: Event-based Video Frame Interpolation
    :star:code:house:project:tv:video
• 视频语言学习（video-and-language learning）
  • Less is More: CLIPBERT for Video-and-Language Learning via Sparse Sampling
    :open_mouth:oral:star:code
    
• 视频预测
  • Greedy Hierarchical Variational Autoencoders for Large-Scale Video Prediction
    :house:project:tv:video
  • Learning Semantic-Aware Dynamics for Video Prediction
  • Video Prediction Recalling Long-term Motion Context via Memory Alignment Learning
    :star:code
    解读：引入记忆模块，突破长距离依赖视频预测的性能瓶颈
  • Learning Goals from Failure
    :star:code:house:project
  • MotionRNN: A Flexible Model for Video Prediction With Spacetime-Varying Motions
• 视频理解
  • Context-aware Biaffine Localizing Network for Temporal Sentence Grounding
    :star:code
  • Co-Grounding Networks with Semantic Attention for Referring Expression Comprehension in Videos
    :house:project
  • Visual Semantic Role Labeling for Video Understanding
    :house:project
  • Temporal Query Networks for Fine-grained Video Understanding
    :open_mouth:oral:house:project
  • Shot Contrastive Self-Supervised Learning for Scene Boundary Detection
  • FrameExit: Conditional Early Exiting for Efficient Video Recognition
    :open_mouth:oral
  • Towards Long-Form Video Understanding
• 视频缩放
  • Video Rescaling Networks with Joint Optimization Strategies for Downscaling and Upscaling
    :star:code:house:project
• 视频异常检测
  • MIST: Multiple Instance Self-Training Framework for Video Anomaly Detection
  • Learning Normal Dynamics in Videos With Meta Prototype Network
    :star:code
    又好又快的视频异常检测，引入元学习的动态原型学习组件
  • Anomaly Detection in Video via Self-Supervised and Multi-Task Learning
• 视频声源定位
  • Localizing Visual Sounds the Hard Way
    :star:code:house:project
• 视频分析
  • Self-Supervised Learning for Semi-Supervised Temporal Action Proposal
    :star:code
• 视频生成
  • Playable Video Generation
    :open_mouth:oral:star:code:house:project:tv:video
  • One-Shot Free-View Neural Talking-Head Synthesis for Video Conferencing
    :open_mouth:oral:star:code:house:project:tv:video
    解读：颠覆视频压缩的不一定是新压缩算法，而可能是GAN！英伟达新算法最高压缩90%流量
    Nvidia的新研究，使用人脸关键点+GAN重建视频通话，相比传统的H.264节省90%流量。代码未开源，但英伟达的GAN框架开源了。
• 视频视角切换
  • Ego-Exo: Transferring Visual Representations from Third-person to First-person Videos
• Action Selection Learning
  • Weakly Supervised Action Selection Learning in Video
    :star:code
• 视频描述
  • Towards Diverse Paragraph Captioning for Untrimmed Videos
    :star:code
• 视频分类
  • Over-the-Air Adversarial Flickering Attacks Against Video Recognition Networks
    :star:code
• 视频字幕
  • Sketch, Ground, and Refine: Top-Down Dense Video Captioning
    :star:code
• Video Grounding
  • Cascaded Prediction Network via Segment Tree for Temporal Video Grounding
  • Interventional Video Grounding With Dual Contrastive Learning
• 视频修复
  • Progressive Temporal Feature Alignment Network for Video Inpainting
    :star:code
    作者提出 Progressive Temporal Feature Alignment Network，利用光流从相邻帧中提取的特征逐步丰富当前帧的特征。纠正了时空特征传播阶段的 spatial misalignment，极大地提高了 inpainted videos 的视觉质量和时空一致性。在 DAVIS 和 FVI 数据集上实现了与现有深度学习方法相比的最先进性能。
  • Restore From Restored: Video Restoration With Pseudo Clean Video
    :star:code
• 视频去模糊化
  • Gated Spatio-Temporal Attention-Guided Video Deblurring
• 视频去噪
  • Efficient Multi-Stage Video Denoising With Recurrent Spatio-Temporal Fusion
• 视频质量评估
  • Patch-VQ: 'Patching Up' the Video Quality Problem
    :house:project
• 视频动作计数
  • Repetitive Activity Counting by Sight and Sound
    :star:code:tv:video
• 视频稳定
• 3D Video Stabilization With Depth Estimation by CNN-Based Optimization
  :tv:video
• Real-Time Selfie Video Stabilization
  :star:code
• 视频去雨
  • Self-Aligned Video Deraining With Transmission-Depth Consistency
  • Semi-Supervised Video Deraining With Dynamical Rain Generator
    :star:code
• video looping technique
  • Animating Pictures with Eulerian Motion Fields
    :house:project:tv:video
• 视频识别
  • 2D or not 2D? Adaptive 3D Convolution Selection for Efficient Video Recognition
  • MoViNets: Mobile Video Networks for Efficient Video Recognition
    :star:code
• 行为识别
  • Multi-Label Activity Recognition using Activity-specific Features and Activity Correlations
• 视频表征学习
  • Spatiotemporal Contrastive Video Representation Learning
    :star:code
  • Removing the Background by Adding the Background: Towards Background Robust Self-Supervised Video Representation Learning
• 视频编码
  • Deep Perceptual Preprocessing for Video Coding

25.3D(三维视觉)

• A Deep Emulator for Secondary Motion of 3D Characters
  :open_mouth:oral:house:project
• Neural Deformation Graphs for Globally-consistent Non-rigid Reconstruction
  :open_mouth:oral:house:project:tv:video
  
• Deep Implicit Templates for 3D Shape Representation
  :open_mouth:oral:star:code:house:project:tv:video
  CVPR 2021 Oral，清华学者提出Deep Implicit Templates，极大扩展DIF能力
  
• SMPLicit: Topology-aware Generative Model for Clothed People
  :house:project
• Picasso: A CUDA-based Library for Deep Learning over 3D Meshes
  :star:code
• Semi-supervised Synthesis of High-Resolution Editable Textures for 3D Humans

• RGB-D Local Implicit Function for Depth Completion of Transparent Objects
  :house:project
• Deep Two-View Structure-from-Motion Revisited
• Deformed Implicit Field: Modeling 3D Shapes with Learned Dense Correspondence
• S3: Neural Shape, Skeleton, and Skinning Fields for 3D Human Modeling
• Deep Polarization Imaging for 3D Shape and SVBRDF Acquisition
  :open_mouth:oral:house:project:tv:video
• Learning Feature Aggregation for Deep 3D Morphable Models
  :star:code
• Plan2Scene: Converting Floorplans to 3D Scenes
  :star:code:house:project:tv:video
• View Generalization for Single Image Textured 3D Models
  :house:project:tv:video
• Mirror3D: Depth Refinement for Mirror Surfaces
  :star:code:house:project
• Learning To Recover 3D Scene Shape From a Single Image
  :star:code
• Normal Integration via Inverse Plane Fitting With Minimum Point-to-Plane Distance
  :star:code
• Shelf-Supervised Mesh Prediction in the Wild
  :house:project
• Unsupervised Learning of 3D Object Categories From Videos in the Wild
• DeepVideoMVS: Multi-View Stereo on Video With Recurrent Spatio-Temporal Fusion
  :star:code:tv:video
• NeuroMorph: Unsupervised Shape Interpolation and Correspondence in One Go
• Learning Monocular 3D Reconstruction of Articulated Categories From Motion
  :star:code:house:project
• Deep Active Surface Models
• Neural Splines: Fitting 3D Surfaces With Infinitely-Wide Neural Networks
  :open_mouth:oral:star:code
• Learning View Selection for 3D Scenes
• StruMonoNet: Structure-Aware Monocular 3D Prediction
• Physically-Aware Generative Network for 3D Shape Modeling
• Hybrid Rotation Averaging: A Fast and Robust Rotation Averaging Approach
• DeepSurfels: Learning Online Appearance Fusion
  :star:code:house:project:tv:video
• 深度估计
  • PLADE-Net: Towards Pixel-Level Accuracy for Self-Supervised Single-View Depth Estimation with Neural Positional Encoding and Distilled Matting Loss
  • Beyond Image to Depth: Improving Depth Prediction using Echoes
    :star:code:house:project
  • Learning High Fidelity Depths of Dressed Humans by Watching Social Media Dance Videos
    :open_mouth:oral:star:code:house:project:tv:video
  • LED2-Net: Monocular 360 Layout Estimation via Differentiable Depth Rendering
    :open_mouth:oral:star:code:house:project
  • S2R-DepthNet: Learning a Generalizable Depth-specific Structural Representation
    :open_mouth:oral
  • Depth Completion with Twin Surface Extrapolation at Occlusion Boundaries
    :star:code
  • Self-supervised Learning of Depth Inference for Multi-view Stereo
    :star:code
  • SMD-Nets: Stereo Mixture Density Networks
    :star:code
  • The Temporal Opportunist: Self-Supervised Multi-Frame Monocular Depth
    :star:code
  • Single Image Depth Estimation using Wavelet Decomposition
    :star:code
  • Differentiable Diffusion for Dense Depth Estimation from Multi-view Images
    :star:code:house:project:tv:video
  • SliceNet: Deep Dense Depth Estimation From a Single Indoor Panorama Using a Slice-Based Representation
  • AdaBins: Depth Estimation Using Adaptive Bins
  • Sparse Auxiliary Networks for Unified Monocular Depth Prediction and Completion
    :star:code
  • S3: Learnable Sparse Signal Superdensity for Guided Depth Estimation
  • LED2-Net: Monocular 360deg Layout Estimation via Differentiable Depth Rendering
    :open_mouth:oral:star:code:house:project
  • Multi-view Depth Estimation using Epipolar Spatio-Temporal Networks
  • Robust Consistent Video Depth Estimation
    :house:project:tv:video
  • 单目深度估计
    • Monocular Depth Estimation via Listwise Ranking Using the Plackett-Luce Model
    • Boosting Monocular Depth Estimation Models to High-Resolution via Content-Adaptive Multi-Resolution Merging
      :star:code:house:project:tv:video
    • 3D Packing for Self-Supervised Monocular Depth Estimation
      :open_mouth:oral:star:code
  • 深度预测
    • Single Image Depth Prediction With Wavelet Decomposition
      :star:code
• 三维重建
  • Deep Implicit Moving Least-Squares Functions for 3D Reconstruction
    :star:code
  • Bilevel Online Adaptation for Out-of-Domain Human Mesh Reconstruction
    :house:project
  • Learning Parallel Dense Correspondence from Spatio-Temporal Descriptors for Efficient and Robust 4D Reconstruction
    :star:code
  • Fostering Generalization in Single-view 3D Reconstruction by Learning a Hierarchy of Local and Global Shape Priors
  • NeuralRecon: Real-Time Coherent 3D Reconstruction from Monocular Video
    :open_mouth:oral:star:code:house:project
  • Fully Understanding Generic Objects: Modeling, Segmentation, and Reconstruction
    :star:code:house:project:tv:video
  • CodedStereo: Learned Phase Masks for Large Depth-of-field Stereo
    :open_mouth:oral
  • SCALE: Modeling Clothed Humans with a Surface Codec of Articulated Local Elements
    :house:project:tv:video
  • LASR: Learning Articulated Shape Reconstruction from a Monocular Video
    :house:project
  • Sketch2Model: View-Aware 3D Modeling from Single Free-Hand Sketches
  • Birds of a Feather: Capturing Avian Shape Models from Images
    :house:project:tv:video
  • Multi-view 3D Reconstruction of a Texture-less Smooth Surface of Unknown Generic Reflectance
    :star:code
  • Generative PointNet: Deep Energy-Based Learning on Unordered Point Sets for 3D Generation, Reconstruction and Classification
    :star:code:house:project
  • From Points to Multi-Object 3D Reconstruction
  • DI-Fusion: Online Implicit 3D Reconstruction With Deep Priors
    :star:code
  • D2IM-Net: Learning Detail Disentangled Implicit Fields From Single Images
  • Residential Floor Plan Recognition and Reconstruction
  • Indoor Panorama Planar 3D Reconstruction via Divide and Conquer
  • Single-View 3D Object Reconstruction from Shape Priors in Memory
  • Deep Optimized Priors for 3D Shape Modeling and Reconstruction
  • MonoRec: Semi-Supervised Dense Reconstruction in Dynamic Environments from a Single Moving Camera
    :star:code:house:project:tv:video
  • PluckerNet: Learn to Register 3D Line Reconstructions
  • 三维网格重建
    • Self-Supervised 3D Mesh Reconstruction From Single Images
• 语义场景补全
  • Semantic Scene Completion via Integrating Instances and Scene in-the-Loop
    :star:code
• 三维关键点
  • KeypointDeformer: Unsupervised 3D Keypoint Discovery for Shape Control
    :open_mouth:oral:star:code:house:project:tv:video
• 三维形状补全
  • Unsupervised 3D Shape Completion through GAN Inversion
    :star:code:house:project
• 三维形状适配
  • Cuboids Revisited: Learning Robust 3D Shape Fitting to Single RGB Images
    :star:code
• 三维压缩
  • Neural 3D Scene Compression via Model Compression
• Stereo Matching-立体匹配
  • A Decomposition Model for Stereo Matching
• Depth Completion-深度补全
  • Depth Completion using Plane-Residual Representation
  • Radar-Camera Pixel Depth Association for Depth Completion
    :star:code
• 三维网格
  • DeepMetaHandles: Learning Deformation Meta-Handles of 3D Meshes With Biharmonic Coordinates
    :open_mouth:oral:star:code
• 3D形状
  • DECOR-GAN: 3D Shape Detailization by Conditional Refinement
    :star:code:tv:oral video:tv:demo
• depth map fusion
  • NeuralFusion: Online Depth Fusion in Latent Space
• 网格重建
  • Learning Delaunay Surface Elements for Mesh Reconstruction
    :star:code
• 3D morphable model(三维形变模型)
  • i3DMM: Deep Implicit 3D Morphable Model of Human Heads
    :house:project:tv:video

24.Reinforcement Learning(强化学习)

• Hierarchical and Partially Observable Goal-driven Policy Learning with Goals Relational Graph
  :star:code:house:project
• Unsupervised Learning for Robust Fitting:A Reinforcement Learning Approach
• Unsupervised Visual Attention and Invariance for Reinforcement Learning

• Unsupervised Learning for Robust Fitting: A Reinforcement Learning Approach
  :star:code
• Iterative Shrinking for Referring Expression Grounding Using Deep Reinforcement Learning
  :star:code

23.Autonomous Driving(自动驾驶)

• Patch-NetVLAD: Multi-Scale Fusion of Locally-Global Descriptors for Place Recognition
  :star:code
  ECCV 2020 Facebook Mapillary Visual Place Recognition Challenge 冠军方案
• AdvSim: Generating Safety-Critical Scenarios for Self-Driving Vehicles
• Self-Supervised Pillar Motion Learning for Autonomous Driving
  :star:code
• Learning by Watching
• Binary TTC: A Temporal Geofence for Autonomous Navigation
  :star:code:tv:video

• GeoSim: Realistic Video Simulation via Geometry-Aware Composition for Self-Driving
  :open_mouth:oral:house:project:tv:video
• 车道线预测
  • LaPred: Lane-Aware Prediction of Multi-Modal Future Trajectories of Dynamic Agents
  • Divide-and-Conquer for Lane-Aware Diverse Trajectory Prediction
    :open_mouth:oral
  • Focus on Local: Detecting Lane Marker from Bottom Up via Key Point
  • Keep your Eyes on the Lane: Real-time Attention-guided Lane Detection
    :star:code
• 轨迹预测
  • SGCN:Sparse Graph Convolution Network for Pedestrian Trajectory Prediction
    :star:code
  • Pedestrian and Ego-Vehicle Trajectory Prediction From Monocular Camera
    :star:code
  • Trajectory Prediction With Latent Belief Energy-Based Model
    :star:code
  • Shared Cross-Modal Trajectory Prediction for Autonomous Driving
    :open_mouth:oral
• 人体轨迹预测
  • Interpretable Social Anchors for Human Trajectory Forecasting in Crowds
  • Introvert: Human Trajectory Prediction via Conditional 3D Attention
  • SGCN: Sparse Graph Convolution Network for Pedestrian Trajectory Prediction
    :star:code
• 交通场景
  • SceneGen: Learning To Generate Realistic Traffic Scenes
• 车辆重识别
  • PhD Learning: Learning With Pompeiu-Hausdorff Distances for Video-Based Vehicle Re-Identification
• HD map reconstruction
  • Projecting Your View Attentively: Monocular Road Scene Layout Estimation via Cross-View Transformation
• HD 图生成
  • HDMapGen: A Hierarchical Graph Generative Model of High Definition Maps
• 车辆检测
  • Robust Multimodal Vehicle Detection in Foggy Weather Using Complementary Lidar and Radar Signals
    :star:code
• 车辆姿态估计
  • Exploring intermediate representation for monocular vehicle pose estimation
    :star:code

22.Medical Imaging(医学影像)

• 3D Graph Anatomy Geometry-Integrated Network for Pancreatic Mass Segmentation, Diagnosis, and Quantitative Patient Management
  用纯多模态 CT 影像可替代目前 JHMI 的需要做肿瘤化学检测和 DNA 测序+医学影像的综合多模态诊断流程，从诊断准确度上有可比较性，定量诊断精度更优
  
• Deep Lesion Tracker: Monitoring Lesions in 4D Longitudinal Imaging Studies
  :star:code
  肿瘤影像里面智能 PACS 辅助医生读片的重要功能
  
• Automatic Vertebra Localization and Identification in CT by Spine Rectification and Anatomically-constrained Optimization
  基于CT 影像的骨折/骨质疏松系统
  
• Multi-institutional Collaborations for Improving Deep Learning-based Magnetic Resonance Image Reconstruction Using Federated Learning
  :star:code
  多机构合作，利用联合学习改进基于深度学习的磁共振图像重建技术
  
• DeepTag: An Unsupervised Deep Learning Method for Motion Tracking on Cardiac Tagging Magnetic Resonance Images
  :open_mouth:oral:star:code
  DeepTag: 一种无监督的深度学习方法，用于心脏标记磁共振图像的运动跟踪
  
• Multiple Instance Captioning: Learning Representations from Histopathology Textbooks and Articles

• XProtoNet: Diagnosis in Chest Radiography with Global and Local Explanations
• Exploring and Distilling Posterior and Prior Knowledge for Radiology Report Generation
• 医学图像分割
  • FedDG: Federated Domain Generalization on Medical Image Segmentation via Episodic Learning in Continuous Frequency Space
    :star:code
  • DoDNet: Learning to segment multi-organ and tumors from multiple partially labeled datasets
    :star:code:sunflower:dataset
  • DiNTS: Differentiable Neural Network Topology Search for 3D Medical Image Segmentation
    :open_mouth:oral
  • DARCNN: Domain Adaptive Region-based Convolutional Neural Network for Unsupervised Instance Segmentation in Biomedical Images
    
  • Every Annotation Counts: Multi-label Deep Supervision for Medical Image Segmentation
  • Learning Calibrated Medical Image Segmentation via Multi-Rater Agreement Modeling
    :star:code
  • clDice - A Novel Topology-Preserving Loss Function for Tubular Structure Segmentation
• 医学图像合成
  • Brain Image Synthesis with Unsupervised Multivariate Canonical CSCℓ4Net
    :open_mouth:oral
  • Brain Image Synthesis with Unsupervised Multivariate Canonical CSCℓ4Net
• 手术技能评估
  • Towards Unified Surgical Skill Assessment
    :star:code
• 微创手术
  • Minimally Invasive Surgery for Sparse Neural Networks in Contrastive Manner
• 放射线报告生成
  • A Self-Boosting Framework for Automated Radiographic Report Generation
  • Exploring and Distilling Posterior and Prior Knowledge for Radiology Report Generation
• MR图像重建
  • MR Image Super-Resolution With Squeeze and Excitation Reasoning Attention Network
  • Joint Deep Model-Based MR Image and Coil Sensitivity Reconstruction Network (Joint-ICNet) for Fast MRI
• 关键点检测与跟踪
  • Reciprocal Landmark Detection and Tracking With Extremely Few Annotations
• X光检测
  • Leveraging Large-Scale Weakly Labeled Data for Semi-Supervised Mass Detection in Mammograms

21.Transformer

• Transformer Interpretability Beyond Attention Visualization
  :star:code
  
• MIST: Multiple Instance Spatial Transformer Network
  :star:code
  试图从热图中进行可微的top-K选择(MIST)（目前在自然图像上也有了一些结果；) 用它可以在没有任何定位监督的情况下进行检测和分类（并不是它唯一能做的事情!）
• Variational Transformer Networks for Layout Generation
• Lesion-Aware Transformers for Diabetic Retinopathy Grading
• Gaussian Context Transformer

• 小样本动作识别
  • Temporal-Relational CrossTransformers for Few-Shot Action Recognition
    :star:code
• 目标检测
  • UP-DETR: Unsupervised Pre-training for Object Detection with Transformers
    :open_mouth:oral:star:code
  • 单样本目标检测
    • Adaptive Image Transformer for One-Shot Object Detection
• 图像处理
  • Pre-Trained Image Processing Transformer
    :star:code:star:gitee
• 人机交互
  • End-to-End Human Object Interaction Detection with HOI Transformer
    :star:code
  • HOTR: End-to-End Human-Object Interaction Detection with Transformers
    :open_mouth:oral
• 图像分割
  • 语义分割
    • Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers
      :star:code:house:project
      基于Transformers从序列到序列的角度重新思考语义分割
      解读：16
      解读：Transformer 在语义分割中的应用，曾位ADE20K 榜首（44.42% mIoU）
    • Embedded Discriminative Attention Mechanism for Weakly Supervised Semantic Segmentation
  • 视频实例分割
    • VisTR: End-to-End Video Instance Segmentation with Transformers
      :open_mouth:oral:star:code
  • 全景分割
    • MaX-DeepLab: End-to-End Panoptic Segmentation With Mask Transformers
• 跟踪
  • Transformer Meets Tracker: Exploiting Temporal Context for Robust Visual Tracking
    :open_mouth:oral:star:code
    more:Transformer再蓄力，跟踪任务中创新高，桥接独立帧，跨帧传递时域信息，CVPR 2021 Oral
  • Transformer Tracking
    :star:code
• 动作预测
  • Multimodal Motion Prediction with Stacked Transformers
    :star:code:house:project:tv:video
• Self-attention自注意力机制
  • Scaling Local Self-Attention For Parameter Efficient Visual Backbones
    :open_mouth:oral
    解读：超越卷积的自注意力模型，谷歌、UC伯克利提出HaloNet
• 检索
  • Revamping Cross-Modal Recipe Retrieval with Hierarchical Transformers and Self-supervised Learning
    :star:code
• 特征匹配
  • LoFTR: Detector-Free Local Feature Matching with Transformers
    :star:code:house:project
• 姿势识别
  • Pose Recognition with Cascade Transformers
    :star:code
• 自动驾驶
  • Multi-Modal Fusion Transformer for End-to-End Autonomous Driving
    :star:code
• 视觉识别
  • Bottleneck Transformers for Visual Recognition
• Video Hashing
  • Self-Supervised Video Hashing via Bidirectional Transformers
    :star:code
• 视觉和语言导航
  • Topological Planning With Transformers for Vision-and-Language Navigation
• 人体姿态与网格重建
  • End-to-End Human Pose and Mesh Reconstruction with Transformers
    :star:code
• 直线段检测
  • Line Segment Detection Using Transformers Without Edges
    :open_mouth:oral:star:code
• 图像分类
  • General Multi-Label Image Classification With Transformers
• 时序语言定位
  • Multi-Stage Aggregated Transformer Network for Temporal Language Localization in Videos
• 场景布局
  • LayoutTransformer: Scene Layout Generation With Conceptual and Spatial Diversity
    :star:code
• 面部动作单元检测
  • Facial Action Unit Detection With Transformers
• 高分辨率图像合成
  • Taming Transformers for High-Resolution Image Synthesis
    :open_mouth:oral:star:code

20.Person Re-Identification(人员重识别)

• Meta Batch-Instance Normalization for Generalizable Person Re-Identification
  :star:code
• Watching You: Global-guided Reciprocal Learning for Video-based Person Re-identification
• Joint Noise-Tolerant Learning and Meta Camera Shift Adaptation for Unsupervised Person Re-Identification
  :star:code
• Intra-Inter Camera Similarity for Unsupervised Person Re-Identification
  :star:code
  论文公开
• Anchor-Free Person Search
  :star:code

• Lifelong Person Re-Identification via Adaptive Knowledge Accumulation
  :star:code
• Group-aware Label Transfer for Domain Adaptive Person Re-identification
  :star:code|code
• Neural Feature Search for RGB-Infrared Person Re-Identification
• Combined Depth Space based Architecture Search For Person Re-identification
• Unsupervised Multi-Source Domain Adaptation for Person Re-Identification
  :open_mouth:oral
• Spatial-Temporal Correlation and Topology Learning for Person Re-Identification in Videos
  :open_mouth:oral
• BiCnet-TKS: Learning Efficient Spatial-Temporal Representation for Video Person Re-Identification
  :star:code
• Generalizable Person Re-identification with Relevance-aware Mixture of Experts
• Person30K: A Dual-Meta Generalization Network for Person Re-Identification
• Prototype-Guided Saliency Feature Learning for Person Search
• UnrealPerson: An Adaptive Pipeline Towards Costless Person Re-Identification
  :star:code
• Learning to Generalize Unseen Domains via Memory-based Multi-Source Meta-Learning for Person Re-Identification
  :star:code
• Farewell to Mutual Information: Variational Distillation for Cross-Modal Person Re-Identification
• Learning 3D Shape Feature for Texture-Insensitive Person Re-Identification
• Partial Person Re-Identification With Part-Part Correspondence Learning
• Coarse-To-Fine Person Re-Identification With Auxiliary-Domain Classification and Second-Order Information Bottleneck
• Unsupervised Pre-Training for Person Re-Identification
• Joint Generative and Contrastive Learning for Unsupervised Person Re-Identification
  :star:code:tv:video
• Wide-Baseline Multi-Camera Calibration Using Person Re-Identification
• Watching You: Global-Guided Reciprocal Learning for Video-Based Person Re-Identification
  :star:code
• Discover Cross-Modality Nuances for Visible-Infrared Person Re-Identification
• Person Re-identification using Heterogeneous Local Graph Attention Networks
• Fine-Grained Shape-Appearance Mutual Learning for Cloth-Changing Person Re-Identification
• 拥挤人群计数
  • Cross-Modal Collaborative Representation Learning and a Large-Scale RGBT Benchmark for Crowd Counting
    :star:code:house:project
  • Cross-View Cross-Scene Multi-View Crowd Counting
  • A Generalized Loss Function for Crowd Counting and Localization
• 基于 Transformer
  • Diverse Part Discovery: Occluded Person Re-identification with Part-Aware Transformer
• 行人检测
  • Variational Pedestrian Detection
  • Generalizable Pedestrian Detection: The Elephant in the Room
    :star:code
• 行人跟踪
  • Tracking Pedestrian Heads in Dense Crowd
    :star:code:house:project
• 步态识别
  • Cross-View Gait Recognition With Deep Universal Linear Embeddings

19.Quantization/Pruning/Knowledge Distillation/Model Compression(量化、剪枝、蒸馏、模型压缩/扩展与优化)

• Learning Student Networks in the Wild
  :star:code
• ReXNet: Diminishing Representational Bottleneck on Convolutional Neural Network
  :star:code
  
• RepVGG: Making VGG-style ConvNets Great Again
  :star:code
  
• Coordinate Attention for Efficient Mobile Network Design
  :star:code

• 剪枝
  • Manifold Regularized Dynamic Network Pruning
  • Neural Response Interpretation through the Lens of Critical Pathways
    :star:code|code
  • Riggable 3D Face Reconstruction via In-Network Optimization
    :star:code
  • Towards Compact CNNs via Collaborative Compression
  • BCNet: Searching for Network Width with Bilaterally Coupled Network
  • The Lottery Ticket Hypothesis for Object Recognition
  • Network Pruning via Performance Maximization
  • Convolutional Neural Network Pruning With Structural Redundancy Reduction
• 模型扩展
  • Fast and Accurate Model Scaling
    :star:code
• 量化
  • Learnable Companding Quantization for Accurate Low-bit Neural Networks
  • Diversifying Sample Generation for Accurate Data-Free Quantization
  • Zero-shot Adversarial Quantization
    :open_mouth:oral:star:code
  • Network Quantization with Element-wise Gradient Scaling
    :star:code:house:project
  • Automated Log-Scale Quantization for Low-Cost Deep Neural Networks
  • Optimal Quantization Using Scaled Codebook
  • QPP: Real-Time Quantization Parameter Prediction for Deep Neural Networks
  • Distribution-Aware Adaptive Multi-Bit Quantization
  • Scalability vs. Utility: Do We Have to Sacrifice One for the Other in Data Importance Quantification?
    :star:code
  • Permute, Quantize, and Fine-Tune: Efficient Compression of Neural Networks
    :star:code
• 知识蒸馏
  • Refine Myself by Teaching Myself: Feature Refinement via Self-Knowledge Distillation
    :star:code
  • Complementary Relation Contrastive Distillation
  • Distilling Knowledge via Knowledge Review
    :star:code
  • Learning From the Master: Distilling Cross-Modal Advanced Knowledge for Lip Reading
  • Multi-Scale Aligned Distillation for Low-Resolution Detection
    :star:code
  • Tree-Like Decision Distillation
  • Revisiting Knowledge Distillation: An Inheritance and Exploration Framework
  • Wasserstein Contrastive Representation Distillation
  • Improving Weakly Supervised Visual Grounding by Contrastive Knowledge Distillation
  • EvDistill: Asynchronous Events To End-Task Learning via Bidirectional Reconstruction-Guided Cross-Modal Knowledge Distillation
• 可逆神经网络
  • Neural Parts: Learning Expressive 3D Shape Abstractions with Invertible Neural Networks
    :house:project
• 模型压缩
  • CDFI: Compression-Driven Network Design for Frame Interpolation
    :star:code
  • Towards Efficient Tensor Decomposition-Based DNN Model Compression With Optimization Framework
• 模型优化
  • Rethinking Channel Dimensions for Efficient Model Design
    :star:code

18.Aerial/Drones/Satellite/RS Image(航空影像/无人机)

• UAV-Human: A Large Benchmark for Human Behavior Understanding with Unmanned Aerial Vehicles
• Detection, Tracking, and Counting Meets Drones in Crowds: A Benchmark
  :star:code
• SIPSA-Net: Shift-Invariant Pan Sharpening with Moving Object Alignment for Satellite Imagery
  :star:code

• 航空影像分割
  • PointFlow: Flowing Semantics Through Points for Aerial Image Segmentation
    :star:code
• 航空影像检测
  • ReDet: A Rotation-equivariant Detector for Aerial Object Detection
    :star:code
• 无人机检测
  • Dogfight: Detecting Drones from Drones Videos
• 多视角卫星摄影测量
  • Shadow Neural Radiance Fields for Multi-view Satellite Photogrammetry

17.Super-Resolution(超分辨率)

• Data-Free Knowledge Distillation For Image Super-Resolution
  :star:code
• AdderSR: Towards Energy Efficient Image Super-Resolution
  :star:code
  
• Cross-MPI: Cross-scale Stereo for Image Super-Resolution using Multiplane Images
  :house:project:tv:video
  CVPR 2021，Cross-MPI以底层场景结构为线索的端到端网络，在大分辨率（x8）差距下也可完成高保真的超分辨率
• ClassSR: A General Framework to Accelerate Super-Resolution Networks by Data Characteristic
  :star:code

• Robust Reference-based Super-Resolution via C²-Matching
  :star:code
• GLEAN: Generative Latent Bank for Large-Factor Image Super-Resolution
  :open_mouth:oral:house:project
  解读：CVPR 2021 Oral | GLEAN: 基于隐式生成库的高倍率图像超分辨率
• BasicVSR: The Search for Essential Components in Video Super-Resolution and Beyond
  :star:code:house:project
• Temporal Modulation Network for Controllable Space-Time Video Super-Resolution
  :star:code作者主页
  基于时空特征可控插值的视频超分辨率网络
  解读：18
• Unsupervised Degradation Representation Learning for Blind Super-Resolution
  :star:code
• SRWarp: Generalized Image Super-Resolution under Arbitrary Transformation
  :star:code
• MASA-SR: Matching Acceleration and Spatial Adaptation for Reference-Based Image Super-Resolution
  :star:code
  作者提出用于 RefSR 的新方法：MASA 网络，包含两个新设计的模块。其中 Match （匹配）和 Extraction（提取）模块大大降低了计算成本。Spatial Adaptation（空间适应）模块用来学习 LR 和 Ref 图像之间的分布差异，并以空间适应的方式将参考特征的分布 remaps（重新映射）为 LR特征的分布。以此更加鲁棒地处理不同的参考图像。
• Towards Fast and Accurate Real-World Depth Super-Resolution: Benchmark Dataset and Baseline
• Exploring Sparsity in Image Super-Resolution for Efficient Inference
  :star:code
• Neural Side-by-Side: Predicting Human Preferences for No-Reference Super-Resolution Evaluation
  :star:code
• Tackling the Ill-Posedness of Super-Resolution Through Adaptive Target Generation
  :star:code
• LAU-Net: Latitude Adaptive Upscaling Network for Omnidirectional Image Super-Resolution
  :star:code
• Image Super-Resolution With Non-Local Sparse Attention
• Unsupervised Real-World Image Super Resolution via Domain-Distance Aware Training
  :star:code
• Single Pair Cross-Modality Super Resolution
• End-to-End Learning for Joint Image Demosaicing, Denoising and Super-Resolution
• Learning Scene Structure Guidance via Cross-Task Knowledge Transfer for Single Depth Super-Resolution
• Deep Burst Super-Resolution
• Light Field Super-Resolution With Zero-Shot Learning
• Fast Bayesian Uncertainty Estimation and Reduction of Batch Normalized Single Image Super-Resolution Network
  :star:code:house:project
• Practical Single-Image Super-Resolution Using Look-Up Table
  :star:code
• Interpreting Super-Resolution Networks With Local Attribution Maps
• Scene Text Telescope: Text-Focused Scene Image Super-Resolution
• 盲超分辨
  • Learning the Non-Differentiable Optimization for Blind Super-Resolution
  • Flow-based Kernel Prior with Application to Blind Super-Resolution
    :star:code
  • KOALAnet: Blind Super-Resolution Using Kernel-Oriented Adaptive Local Adjustment
• 视频超分辨率
  • Space-Time Distillation for Video Super-Resolution
  • Turning Frequency to Resolution: Video Super-Resolution via Event Cameras

16.Visual Question Answering(视觉问答)

• Counterfactual VQA: A Cause-Effect Look at Language Bias
  :star:code
• AGQA: A Benchmark for Compositional Spatio-Temporal Reasoning
  :house:project:tv:video
• Domain-robust VQA with diverse datasets and methods but no target labels
  :house:project
• Found a Reason for me? Weakly-supervised Grounded Visual Question Answering using Capsules
  :star:code
• Perception Matters: Detecting Perception Failures of VQA Models Using Metamorphic Testing
• Roses Are Red, Violets Are Blue... but Should VQA Expect Them To?
  :sunflower:dataset
• Predicting Human Scanpaths in Visual Question Answering
• Separating Skills and Concepts for Novel Visual Question Answering
  :star:code
• How Transferable Are Reasoning Patterns in VQA?
  :star:code:house:project:tv:video
• Explicit Knowledge Incorporation for Visual Reasoning
• KRISP: Integrating Implicit and Symbolic Knowledge for Open-Domain Knowledge-Based VQA
• Image-Text Matching
  • Discrete-Continuous Action Space Policy Gradient-Based Attention for Image-Text Matching
• 视频问答
  • TrafficQA: A Question Answering Benchmark and an Efficient Network for Video Reasoning over Traffic Events
    :star:code
  • Bridge to Answer: Structure-aware Graph Interaction Network for Video Question Answering
  • NExT-QA: Next Phase of Question-Answering to Explaining Temporal Actions
    :star:code
  • Look Before You Speak: Visually Contextualized Utterances
• 交通相关VQA
  • SUTD-TrafficQA: A Question Answering Benchmark and an Efficient Network for Video Reasoning Over Traffic Events
    :star:code

15.GAN

• Exploiting Spatial Dimensions of Latent in GAN for Real-time Image Editing
  :star:code
• Hijack-GAN: Unintended-Use of Pretrained, Black-Box GANs
  :star:code
• Efficient Conditional GAN Transfer with Knowledge Propagation across Classes
  :star:code
• Anycost GANs for Interactive Image Synthesis and Editing
  :star:code:house:project:tv:video
  Anycost GAN，可适应广泛的硬件和延迟要求，以及实现交互式图像编辑
• TediGAN: Text-Guided Diverse Image Generation and Manipulation
  :star:code:house:project:tv:video
• Generative Hierarchical Features from Synthesizing Images
  :open_mouth:oral:star:code:house:project
  作者称预训练 GAN 生成器可以当作是一种学习的多尺度损失。用它进行训练可以带来高度竞争的层次化和分离的视觉特征，称之为生成层次化特征（GH-Feat）。并进一步表明，GH-Feat不仅有利于生成性任务，更重要的是有利于分辨性任务，包括人脸验证、关键点检测、layout prediction、迁移学习、style mixing、图像编辑等。
• Teachers Do More Than Teach: Compressing Image-to-Image Models
  :star:code
• PISE: Person Image Synthesis and Editing with Decoupled GAN
  :star:code
• LOHO: Latent Optimization of Hairstyles via Orthogonalization
  :star:code
• HumanGAN: A Generative Model of Humans Images
• HistoGAN: Controlling Colors of GAN-Generated and Real Images via Color Histograms
  :star:code
• DivCo: Diverse Conditional Image Synthesis via Contrastive Generative Adversarial Network
  :star:code

• pi-GAN: Periodic Implicit Generative Adversarial Networks for 3D-Aware Image Synthesis
  :open_mouth:oral:house:project:tv:video
  更多：斯坦福学者提出周期性隐式生成对抗网络（π-GAN或pi-GAN），用于高质量的3D感知图像合成
  斯坦福大学
• ReMix: Towards Image-to-Image Translation with Limited Data
• Unsupervised Disentanglement of Linear-Encoded Facial Semantics
• Content-Aware GAN Compression
• Regularizing Generative Adversarial Networks under Limited Data
  :star:code:house:project
• Where and What? Examining Interpretable Disentangled Representations
  :star:code
• Few-shot Image Generation via Cross-domain Correspondence
  :house:project
• DatasetGAN: Efficient Labeled Data Factory with Minimal Human Effort
  :open_mouth:oral
• Surrogate Gradient Field for Latent Space Manipulation
• StylePeople: A Generative Model of Fullbody Human Avatars
  :house:project
• Ensembling with Deep Generative Views
  :star:code:house:project
• Continuous Face Aging via Self-estimated Residual Age Embedding
• Blur, Noise, and Compression Robust Generative Adversarial Networks
• Adaptive Weighted Discriminator for Training Generative Adversarial Networks
  :star:code
• DatasetGAN: Efficient Labeled Data Factory with Minimal Human Effort
  :house:project
• House-GAN++: Generative Adversarial Layout Refinement Network towards Intelligent Computational Agent for Professional Architects
  :star:code:house:project
• Roof-GAN: Learning To Generate Roof Geometry and Relations for Residential Houses
  :star:code
• Exploring Adversarial Fake Images on Face Manifold
• Hyper-LifelongGAN: Scalable Lifelong Learning for Image Conditioned Generation
• GANmut: Learning Interpretable Conditional Space for Gamut of Emotions
  :star:code
• StyleSpace Analysis: Disentangled Controls for StyleGAN Image Generation
• Positional Encoding As Spatial Inductive Bias in GANs
  :star:code:house:project
• Partition-Guided GANs
• 3D Shape Generation With Grid-Based Implicit Functions
• Linear Semantics in Generative Adversarial Networks
  :star:code:house:project:tv:video
• Cross-Modal Contrastive Learning for Text-to-Image Generation
• Lifting 2D StyleGAN for 3D-Aware Face Generation
• Unsupervised Learning of Depth and Depth-of-Field Effect From Natural Images With Aperture Rendering Generative Adversarial Networks
  :open_mouth:oral:house:project
• Training Generative Adversarial Networks in One Stage
  :star:code
• Self-Supervised Video GANs: Learning for Appearance Consistency and Motion Coherency
• Closed-Form Factorization of Latent Semantics in GANs
  :open_mouth:oral:star:code:house:project:tv:video
• Discovering Interpretable Latent Space Directions of GANs Beyond Binary Attributes
  :star:code
• Normalized Avatar Synthesis Using StyleGAN and Perceptual Refinement
• L2M-GAN: Learning To Manipulate Latent Space Semantics for Facial Attribute Editing
• Spatially-invariant Style-codes Controlled Makeup Transfer
  :star:code
• 无监督图像合成
  • Posterior Promoted GAN With Distribution Discriminator for Unsupervised Image Synthesis
    :star:code
• 图像到图像翻译
  • Memory-guided Unsupervised Image-to-image Translation
  • Image-to-image Translation via Hierarchical Style Disentanglement
    :open_mouth:oral:star:code
    在图像到图像翻译上实现层次风格解耦
  • CoMoGAN: continuous model-guided image-to-image translation
    :open_mouth:oral:star:code
  • Encoding in Style: a StyleGAN Encoder for Image-to-Image Translation
    :star:code:house:project
    
• 图像编辑
  • StyleMapGAN: Exploiting Spatial Dimensions of Latent in GAN for Real-time Image Editing
    :star:code:tv:video
  • Navigating the GAN Parameter Space for Semantic Image Editing
    :star:code
• 人脸图像合成
  • TediGAN: Text-Guided Diverse Face Image Generation and Manipulation
    :star:code:tv:video

14.Few-Shot/Zero-Shot Learning,Domain Generalization/Adaptation(小/零样本学习，域适应，域泛化)

• 小样本学习
  • Exploring Complementary Strengths of Invariant and Equivariant Representations for Few-Shot Learning
    
  • Learning Dynamic Alignment via Meta-filter for Few-shot Learning
    作者主页
    通过元卷积核实现基于动态对齐的小样本学习
    解读：17
  • ECKPN: Explicit Class Knowledge Propagation Network for Transductive Few-shot Learning
  • Mutual CRF-GNN for Few-Shot Learning
  • Rethinking Class Relations: Absolute-Relative Supervised and Unsupervised Few-Shot Learning
  • Pareto Self-Supervised Training for Few-Shot Learning
  • Reinforced Attention for Few-Shot Learning and Beyond
  • Using Shape to Categorize: Low-Shot Learning with an Explicit Shape Bias
    :house:project
  • Prototype Completion With Primitive Knowledge for Few-Shot Learning
    :star:code
• 域泛化
  • FSDR: Frequency Space Domain Randomization for Domain Generalization
    受 JPEG 将空间图像转换为多个频率分量(FCs)的启发，提出频率空间域随机化(FSDR)，通过保留域变量FCs(DIFs)和只随机化域变量FCs(DVFs)来随机化频率空间的图像。
  • Domain Generalization via Inference-time Label-Preserving Target Projections
  • Adaptive Methods for Real-World Domain Generalization
    :open_mouth: Oral
  • Progressive Domain Expansion Network for Single Domain Generalization
    :star:code
  • A Fourier-based Framework for Domain Generalization
    :open_mouth:oral:star:code
  • Adversarially Adaptive Normalization for Single Domain Generalization
  • Generalization on Unseen Domains via Inference-Time Label-Preserving Target Projections
  • Uncertainty-Guided Model Generalization to Unseen Domains
    :star:code
  • Open Domain Generalization with Domain-Augmented Meta-Learning
• 零样本学习
  • Goal-Oriented Gaze Estimation for Zero-Shot Learning
    :star:code
  • Contrastive Embedding for Generalized Zero-Shot Learning
    :star:code
  • Open World Compositional Zero-Shot Learning
  • Learning Graph Embeddings for Compositional Zero-Shot Learning
    :star:code
  • Hardness Sampling for Self-Training Based Transductive Zero-Shot Learning
    :star:code
• 域适应
  • Dynamic Transfer for Multi-Source Domain Adaptation
    :star:code
  • Transferable Semantic Augmentation for Domain Adaptation
    :star:code
  • MetaAlign: Coordinating Domain Alignment and Classification for Unsupervised Domain Adaptation
  • DRANet: Disentangling Representation and Adaptation Networks for Unsupervised Cross-Domain Adaptation
  • Dynamic Domain Adaptation for Efficient Inference
    :star:code
  • Prototypical Cross-domain Self-supervised Learning for Few-shot Unsupervised Domain Adaptation
    :house:project
  • Domain Consensus Clustering for Universal Domain Adaptation
    :star:code
  • Divergence Optimization for Noisy Universal Domain Adaptation
  • Curriculum Graph Co-Teaching for Multi-Target Domain Adaptation
    :star:code:house:project
  • Unsupervised Multi-source Domain Adaptation Without Access to Source Data
  • Domain Adaptation with Auxiliary Target Domain-Oriented Classifier
    :star:code
  • Cross-Domain Adaptive Clustering for Semi-Supervised Domain Adaptation
  • Generalized Domain Adaptation
    :star:code
  • Multi-Target Domain Adaptation with Collaborative Consistency Learning
    :star:code
  • Wasserstein Barycenter for Multi-Source Domain Adaptation
  • Conditional Bures Metric for Domain Adaptation
  • Partial Feature Selection and Alignment for Multi-Source Domain Adaptation
  • Transferable Query Selection for Active Domain Adaptation
    :star:code
  • Learning Invariant Representations and Risks for Semi-Supervised Domain Adaptation
    :star:code
  • 无监督域适应
    • Cross-Domain Gradient Discrepancy Minimization for Unsupervised Domain Adaptation
      :star:code
    • Instance Level Affinity-Based Transfer for Unsupervised Domain Adaptation
      :star:code
    • Learning to Relate Depth and Semantics for Unsupervised Domain Adaptation
      :star:code
    • PixMatch: Unsupervised Domain Adaptation via Pixelwise Consistency Training
    • FixBi: Bridging Domain Spaces for Unsupervised Domain Adaptation
      :star:code
    • Dynamic Weighted Learning for Unsupervised Domain Adaptation

13.Image/Video Retrieval(图像/视频检索)

• Thinking Fast and Slow: Efficient Text-to-Visual Retrieval with Transformers
• Convolutional Hough Matching
  :open_mouth:oral:house:project
• T2VLAD: Global-Local Sequence Alignment for Text-Video Retrieval
• M3P: Learning Universal Representations via Multitask Multilingual Multimodal Pre-training
• VIGOR: Cross-View Image Geo-localization beyond One-to-one Retrieval
  :star:code
• 图像检索
  • Probabilistic Embeddings for Cross-Modal Retrieval
    :star:code
  • QAIR: Practical Query-efficient Black-Box Attacks for Image Retrieval
  • More Photos are All You Need: Semi-Supervised Learning for Fine-Grained Sketch Based Image Retrieval
    :star:code
  • StyleMeUp: Towards Style-Agnostic Sketch-Based Image Retrieval
  • Prototype-supervised Adversarial Network for Targeted Attack of Deep Hashing
    :star:code
  • CoSMo: Content-Style Modulation for Image Retrieval With Text Feedback
    :star:code
  • Efficient Object Embedding for Spliced Image Retrieval
  • You See What I Want You To See: Exploring Targeted Black-Box Transferability Attack for Hash-Based Image Retrieval Systems
• 视频检索
  • On Semantic Similarity in Video Retrieval
    :star:code:house:project:tv:video
• 视觉搜索
  • Compatibility-aware Heterogeneous Visual Search
• 跨模态检索
  • Multi-Modal Relational Graph for Cross-Modal Video Moment Retrieval
    :house:project
  • Learning Cross-Modal Retrieval With Noisy Labels
  • Cross-Modal Center Loss for 3D Cross-Modal Retrieval
• 检索(三维形状检索和变形的联合学习)
  • Joint Learning of 3D Shape Retrieval and Deformation

12.Image Quality Assessment(图像质量评估)

• 图像恢复Image Restoration
  • Multi-Stage Progressive Image Restoration
    :star:code
    
  • See through Gradients: Image Batch Recovery via GradInversion
  • Controllable Image Restoration for Under-Display Camera in Smartphones
  • Zero-Shot Single Image Restoration Through Controlled Perturbation of Koschmieder's Model
    :house:project
  • High-Quality Stereo Image Restoration From Double Refraction
  • Image Restoration for Under-Display Camera
  • 漫画修复
    • Exploiting Aliasing for Manga Restoration
• 去阴影Shadow Removal
  • Auto-Exposure Fusion for Single-Image Shadow Removal
    :star:code
    
  • From Shadow Generation to Shadow Removal
    :star:code
  • No Shadow Left Behind: Removing Objects and Their Shadows Using Approximate Lighting and Geometry
• 去模糊Deblurring
  • DeFMO: Deblurring and Shape Recovery of Fast Moving Objects
    :star:code:tv:video
    
  • ARVo: Learning All-Range Volumetric Correspondence for Video Deblurring
  • Explore Image Deblurring via Blur Kernel Space
  • Towards Rolling Shutter Correction and Deblurring in Dynamic Scenes
    :star:code
  • Learning a Non-Blind Deblurring Network for Night Blurry Images
  • Ultra-High-Definition Image Dehazing via Multi-Guided Bilateral Learning
  • Test-Time Fast Adaptation for Dynamic Scene Deblurring via Meta-Auxiliary Learning
  • Blind Deblurring for Saturated Images
  • Explore Image Deblurring via Encoded Blur Kernel Space
    :star:code
  • Learning Spatially-Variant MAP Models for Non-Blind Image Deblurring
• 去反射Reflection Removal
  • Robust Reflection Removal with Reflection-free Flash-only Cues
    :star:code
  • Single Image Reflection Removal With Absorption Effect
    :star:code
  • Panoramic Image Reflection Removal
• 去雾
  • Learning to Restore Hazy Video: A New Real-World Dataset and A New Method
    学习复原有雾视频：一种新的真实数据集及算法
    解读：9
  • Contrastive Learning for Compact Single Image Dehazing
    :star:code
    基于对比学习的紧凑图像去雾方法
    解读：5
  • PSD: Principled Synthetic-to-Real Dehazing Guided by Physical Priors
    :star:code
• 去噪Denoising
  • Neighbor2Neighbor: Self-Supervised Denoising from Single Noisy Images
    :star:code
    解读：CVPR 2021 | Neighbor2Neighbor：仅需噪声图像即可训练任意降噪网络的方法
  • NBNet: Noise Basis Learning for Image Denoising with Subspace Projection
    :star:code
    粗解：9
  • Invertible Denoising Network: A Light Solution for Real Noise Removal
    :star:code
  • FBI-Denoiser: Fast Blind Image Denoiser for Poisson-Gaussian Noise
    :star:code
  • Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising
  • The Neural Tangent Link Between CNN Denoisers and Non-Local Filters
    :star:code
  • Deep Denoising of Flash and No-Flash Pairs for Photography in Low-Light Environments
    :house:project
  • Adaptive Consistency Prior Based Deep Network for Image Denoising
  • EventZoom: Learning To Denoise and Super Resolve Neuromorphic Events
    :house:project:tv:video
  • Extreme Low-Light Environment-Driven Image Denoising Over Permanently Shadowed Lunar Regions With a Physical Noise Model
  • Guided Integrated Gradients: An Adaptive Path Method for Removing Noise
  • Effective Snapshot Compressive-Spectral Imaging via Deep Denoising and Total Variation Priors
    :star:code
  • Deep Convolutional Dictionary Learning for Image Denoising
    :star:code
  • Learning An Explicit Weighting Scheme for Adapting Complex HSI Noise
  • Pseudo 3D Auto-Correlation Network for Real Image Denoising
• 去雨Deraining
  • Semi-Supervised Video Deraining with Dynamic Rain Generator
  • Closing the Loop: Joint Rain Generation and Removal via Disentangled Image Translation
  • Robust Representation Learning With Feedback for Single Image Deraining
    :star:code
  • Multi-Decoding Deraining Network and Quasi-Sparsity Based Training
  • Image De-Raining via Continual Learning
  • From Rain Generation to Rain Removal
    :star:code
  • Memory Oriented Transfer Learning for Semi-Supervised Image Deraining
  • Removing Raindrops and Rain Streaks in One Go
  • 控制雨量
    • Controlling the Rain: From Removal to Rendering
• 曝光校正
  • Learning Multi-Scale Photo Exposure Correction
    :star:code
• 图像修复Image Inpainting
  • Generating Diverse Structure for Image Inpainting With Hierarchical VQ-VAE
    :star:code
  • TransFill: Reference-guided Image Inpainting by Merging Multiple Color and Spatial Transformations
    :house:project
  • Image Inpainting with External-internal Learning and Monochromic Bottleneck
    :star:code
  • PD-GAN: Probabilistic Diverse GAN for Image Inpainting
    :star:code
  • Image Inpainting Guided by Coherence Priors of Semantics and Textures
• 图像编辑
  • DeFLOCNet: Deep Image Editing via Flexible Low-level Controls
    :star:code
• 图像压缩
  • Attention-guided Image Compression by Deep Reconstruction of Compressive Sensed Saliency Skeleton
  • Slimmable Compressive Autoencoders for Practical Neural Image Compression
    :star:code
  • Checkerboard Context Model for Efficient Learned Image Compression
  • Learning Scalable ℓ∞-constrained Near-lossless Image Compression via Joint Lossy Image and Residual Compression
    :star:code
  • Deep Homography for Efficient Stereo Image Compression
    :star:code
    分享会
  • iVPF: Numerical Invertible Volume Preserving Flow for Efficient Lossless Compression
  • What's in the Image? Explorable Decoding of Compressed Images
  • Learning Scalable lY=-Constrained Near-Lossless Image Compression via Joint Lossy Image and Residual Compression
  • Asymmetric Gained Deep Image Compression With Continuous Rate Adaptation
• de-rendering
  • De-rendering the World's Revolutionary Artefacts
    :house:project:tv:video
  • How To Exploit the Transferability of Learned Image Compression to Conventional Codecs
• 消除图像伪影
  • Removing Diffraction Image Artifacts in Under-Display Camera via Dynamic Skip Connection Network
    :star:code:house:project
• 图像对齐
  • Deep Lucas-Kanade Homography for Multimodal Image Alignment
    :star:code
• 图像和谐化
  • Region-aware Adaptive Instance Normalization for Image Harmonization
    :star:code
  • Intrinsic Image Harmonization
    :star:code
• 图像增强
  • CAMERAS: Enhanced Resolution and Sanity Preserving Class Activation Mapping for Image Saliency
    :star:code
  • Retinex-Inspired Unrolling With Cooperative Prior Architecture Search for Low-Light Image Enhancement
    :star:code:house:project
  • Debiased Subjective Assessment of Real-World Image Enhancement
  • Learning Temporal Consistency for Low Light Video Enhancement From Single Images
    :star:code
• Image Stabilization防抖
  • Digital Gimbal: End-to-end Deep Image Stabilization with Learnable Exposure Times
• 去散焦模糊
  • Iterative Filter Adaptive Network for Single Image Defocus Deblurring
• 去遮挡
  • Human De-Occlusion: Invisible Perception and Recovery for Humans
    :house:project
• 增强夜间可视度
  • Nighttime Visibility Enhancement by Increasing the Dynamic Range and Suppression of Light Effects
• 图像补全
  • Prior Based Human Completion
• image steganography(图片隐写术)
  • Large-Capacity Image Steganography Based on Invertible Neural Networks
• Image Blending
  • Bridging the Visual Gap: Wide-Range Image Blending
    :star:code
• 图像矫正
  • Progressively Complementary Network for Fisheye Image Rectification Using Appearance Flow
    :star:code
• Defocus Blur Detection(检测由散焦导致的模糊区域)
  • Self-Generated Defocus Blur Detection via Dual Adversarial Discriminators
    :star:code
• 场景恢复（不同天气、成像）
  • Rank-One Prior: Toward Real-Time Scene Recovery
  • ZeroScatter: Domain Transfer for Long Distance Imaging and Vision Through Scattering Media
    :house:project:tv:video
• Image cropping(图片裁剪)
  • Composing Photos Like a Photographer
• Image Stitching(图像拼接)
  • Leveraging Line-Point Consistence To Preserve Structures for Wide Parallax Image Stitching
    :star:code
• 深度估计+图像修复
  • Dual Pixel Exploration: Simultaneous Depth Estimation and Image Restoration
• Image extrapolation
  • OCONet: Image Extrapolation by Object Completion
• 图像编辑
  • Learning by Planning: Language-Guided Global Image Editing
• 图像质量
  • Quality-Agnostic Image Recognition via Invertible Decoder
  • Troubleshooting Blind Image Quality Models in the Wild
    :star:code
• HDR Deghosting(HDR去伪影)
  • [Labeled From Unlabeled: Exploiting Unlabeled Data for Few-Shot Deep HDR Deghosting](https://openaccess.thecvf.com/content/CVPR2021/papers/Prabhakar_Labeled_From_Unlabeled_Exploiting_Unlabeled_Data_for_Few-Shot_Deep_HDR_CVP