Pseudo-Lab/pseudodiffusers

:bulb: PseudoDiffusers: paper/code review and experimental findings related to computer vision generation and diffusion-based models

HTML

44

353 commits

updated Jul 11, 2025

See the code

README

Welcome to PseudoDiffusers!!

This is the repository of PseudoDiffusers team.

:bulb: Our aim is to review papers and code related to computer vision generation models, approach them theoretically, and conduct various experiments by fine-tuning diffusion based models.

About Us - PseudoLab

About Us - PseudoDiffusers

참여 방법: 매주 수요일 오후 9시, 가짜연구소 Discord Room-DH 로 입장!

Publications

DiffInject: Revisiting Debias via Synthetic Data Generation using Diffusion-based Style Injection
Donggeun Ko*, Sangwoo Jo*, Dongjun Lee, Namjun Park, Jaekwang KIM
CVPR 2024 Workshop
PDF

Contributors

Reviewed Papers

idxDatePresenterPaper / Code
12023.03.29Sangwoo JoAuto-Encoding Variational Bayes (ICLR 2014)
Generative Adversarial Networks (NIPS 2014)
22023.04.05Kwangsu Mun
Jisu Kim
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks (ICCV 2017)
A Style-Based Generator Architecture for Generative Adversarial Networks (CVPR 2019)
32023.04.12Beomsoo Park
Seunghwan Ji
Denoising Diffusion Probabilistic Models (NeurIPS 2020)
Denoising Diffusion Implicit Models (ICLR 2021)
42023.05.10Donggeun Sean KoDiffusion Models Beat GANs in Image Synthesis (NeurIPS 2021)
Zero-Shot Text-to-Image Generation (ICML 2021)
52023.05.17Namkyeong Cho
Sangwoo Jo
High-Resolution Image Synthesis with Latent Diffusion Models (CVPR 2022)
DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation (CVPR 2023)
62023.05.24Kwangsu Mun
Jisu Kim
An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion (ICLR 2023)
Adding Conditional Control to Text-to-Image Diffusion Models (ICCV 2023)
72023.05.31Beomsoo Park
Seunghwan Ji
LoRA: Low-Rank Adaptation of Large Language Models (ICLR 2022)
Multi-Concept Customization of Text-to-Image Diffusion (CVPR 2023)
82023.08.30Donggeun Sean Ko
Sangwoo Jo
Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding (NeurIPS 2022)
Imagen Editor and EditBench: Advancing and Evaluating Text-Guided Image Inpainting (CVPR 2023)
92023.09.06SeonHoon Kim
Seunghwan Ji
Hierarchical Text-Conditional Image Generation with CLIP Latents
SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equations (ICLR 2022)
102023.09.13Namkyeong Cho
Junhyoung Lee
DeepFloyd IF
SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis (ICLR 2024 Spotlight)
112023.09.20HyoungSeo Cho
Sangwoo Jo
HyperDreamBooth: HyperNetworks for Fast Personalization of Text-to-Image Models (CVPR 2024)
T2I-Adapter: Learning Adapters to Dig out More Controllable Ability for Text-to-Image Diffusion Models (AAAI 2024)
122023.09.27Sehwan Park
Junhyoung Lee
GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models (PMLR 2022)
Scaling Autoregressive Multi-Modal Models: Pretraining and Instruction Tuning
132023.10.11Jeonghwa Yoo
SeonHoon Kim
Synthetic Data from Diffusion Models Improves ImageNet Classification (TMLR 2023)
Your Diffusion Model is Secretly a Zero-Shot Classifier (ICCV 2023)
142023.10.18Seunghwan JiA Study on the Evaluation of Generative Models
152023.10.25Sangwoo Jo
HyoungSeo Cho
Progressive Distillation for Fast Sampling of Diffusion Models (ICLR 2022 Spotlight)
ConceptLab: Creative Generation using Diffusion Prior Constraints (ACM Transactions on Graphics 2024)
162023.11.01SeonHoon Kim
Jeonghwa Yoo
BBDM: Image-to-image Translation with Brownian Bridge Diffusion Models (CVPR 2023)
Make-A-Video: Text-to-Video Generation without Text-Video Data (ICLR 2023)
172023.11.15Sehwan Park
Junhyoung Lee
Diffusion Models already have a Semantic Latent Space (ICLR 2023)
Align your Latents: High-Resolution Video Synthesis with Latent Diffusion Models (CVPR 2023)
182023.11.29Donggeun Sean KoVideo Diffusion Models (NeurIPS 2022)
192024.03.13Geonhak SongAnimate Anyone: Consistent and Controllable Image-to-Video Synthesis for Character Animation (CVPR Workshop 2023)
DreaMoving: A Human Video Generation Framework based on Diffusion Models (CVPR Workshop 2023)
202024.03.20Junhyoung LeeMuse: Text-To-Image Generation via Masked Generative Transformers (ICML 2023)
212024.03.27Seunghwan JiScaling up GANs for Text-to-Image Synthesis (CVPR 2023)
222024.04.03Sangwoo JoConsistency Models (ICML 2023)
232024.04.24Donghyun HanLatent Consistency Models: Synthesizing High-Resolution Images with Few-Step Inference
242024.05.01Jeonghwa YooDreamPose: Fashion Image-to-Video Synthesis via Stable Diffusion (ICCV 2023)
252024.05.08Sehwan ParkLLM-grounded Diffusion: Enhancing Prompt Understanding of Text-to-Image Diffusion Models with Large Language Models (TMLR 2024)
262024.05.15Kyeongmin YuAnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning (ICLR 2024 Spotlight)
272024.05.22Jeongin LeeNeRF: Representing Scenes as Neural Radiance Fields for View Synthesis (ECCV 2020 Oral)
282024.05.29Hyunsoo Kim3D Gaussian Splatting for Real-Time Radiance Field Rendering (SIGGRAPH 2023)
292024.06.12Donggeun Sean KoDiffInject: Revisiting Debias via Synthetic Data Generation using Diffusion-based Style Injection (CVPR Workshop 2024)
302024.06.26Jeonghwa Yoo
Kyeongmin Yu
Point-E: A System for Generating 3D Point Clouds from Complex Prompts
Shap-E: Generating Conditional 3D Implicit Function
312024.07.03Geonhak SongDreamFusion: Text-to-3D using 2D Diffusion (ICLR 2023)
322024.07.17Sangwoo Jo
Junhyoung Lee
Magic3D: High-Resolution Text-to-3D Content Creation (CVPR 2023)
Scalable Diffusion Models with Transformers (ICCV 2023)
332024.07.24Jeongin Lee
Hyunsoo Kim
DreamBooth3D: Subject-Driven Text-to-3D Generation (ICCV 2023)
Style Aligned Image Generation via Shared Attention (CVPR 2024)
342024.09.18Sangwoo JoOne-step Image Translation with Text-to-Image Models
352024.09.25Joongwon LeeOne-step Diffusion with Distribution Matching Distillation (CVPR 2024)
362024.10.02Donghyun HanLCM-LoRA: A Universal Stable-Diffusion Acceleration Module
372024.10.09Kyeongmin YuIP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Models
382024.10.30Jeongin LeeZero-1-to-3: Zero-shot One Image to 3D Object (ICCV 2023)
392024.11.06Geonhak SongMVDream: Multi-view Diffusion for 3D Generation (ICLR 2024)
402024.11.13Kyeongmin YuProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillation (NeurIPS 2023)
412024.11.27Jeonghwa Yoo
Sangwoo Jo
One-2-3-45: Any Single Image to 3D Mesh in 45 Seconds without Per-Shape Optimization (NeurIPS 2023)
Zero123++: a Single Image to Consistent Multi-view Diffusion Base Model
422024.12.04Joongwon Lee
Donghyun Han
LRM: Large Reconstruction Model for Single Image to 3D (ICLR 2024 Oral)
LGM: Large Multi-View Gaussian Model for High-Resolution 3D Content Creation (ECCV 2024 Oral)
432024.12.11Kyeongmin YuDreamGaussian: Generative Gaussian Splatting for Efficient 3D Content Creation (ICLR 2024 Oral)
442024.12.18Geonhak Song
Donggeun Sean Ko
CAT3D: Create Anything in 3D with Multi-View Diffusion Models (NeurIPS 2024 Oral)
Coin3D: Controllable and Interactive 3D Assets Generation with Proxy-Guided Conditioning (CVPR Workshop 2024)

Jupyter Book Update Procedure

  1. Clone the repo on your local computer
git clone https://github.com/Pseudo-Lab/text-to-image-generation.git
  1. Install required packages
pip install jupyter-book==0.15.1
pip install ghp-import==2.1.0
  1. Change the contents in book/docs folder with the following format and update _toc.yml file accordingly

  • 3.1. Add information section on top of the markdown page
- **Title:** {논문 제목}, {학회/학술지명}

- **Reference**
    - Paper:  [{논문 링크}]({논문 링크})
    - Code: [{code 링크}]({code 링크})
    - Review: [{review 링크}]({review 링크})
    
- **Author:** {리뷰 작성자 기입}

- **Edited by:** {리뷰 편집자 기입}

- **Last updated on {최종 update 날짜 e.g. Apr. 12, 2023}**
  • 3-2. Use the following template when displaying images
:::{figure-md} 
<img src="{주소}" alt="{tag명}" class="bg-primary mb-1" width="{800px}">

{제목} \  (source: {출처})
:::
  • 3-3. Update _toc.yml file accordingly
format: jb-book
root: intro
parts:
- caption: Paper/Code Review
  chapters:
  - file: docs/review/vae
  - file: docs/review/gan
  1. Build the book using Jupyter Book command
jupyter-book build ./book
  1. Sync your local and remote repositories
cd pseudodiffusers
git add .
git commit -m "adding my first book!"
git push
  1. Publish your Jupyter Book with Github Pages
ghp-import -n -p -f book/_build/html -m "initial publishing"
3d-generation
diffusion
image-generation
research
video-generation

Contributors

jasonjo97

153 commits

seanko29

33 commits

egshkim

28 commits

innimu

22 commits

Pseudo-Lab/pseudodiffusers

:bulb: PseudoDiffusers: paper/code review and experimental findings related to computer vision generation and diffusion-based models

HTML

44

353 commits

updated Jul 11, 2025

See the code

README

Welcome to PseudoDiffusers!!

This is the repository of PseudoDiffusers team.

:bulb: Our aim is to review papers and code related to computer vision generation models, approach them theoretically, and conduct various experiments by fine-tuning diffusion based models.

About Us - PseudoLab

About Us - PseudoDiffusers

참여 방법: 매주 수요일 오후 9시, 가짜연구소 Discord Room-DH 로 입장!

Publications

DiffInject: Revisiting Debias via Synthetic Data Generation using Diffusion-based Style Injection
Donggeun Ko*, Sangwoo Jo*, Dongjun Lee, Namjun Park, Jaekwang KIM
CVPR 2024 Workshop
PDF

Contributors

Reviewed Papers

idxDatePresenterPaper / Code
12023.03.29Sangwoo JoAuto-Encoding Variational Bayes (ICLR 2014)
Generative Adversarial Networks (NIPS 2014)
22023.04.05Kwangsu Mun
Jisu Kim
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks (ICCV 2017)
A Style-Based Generator Architecture for Generative Adversarial Networks (CVPR 2019)
32023.04.12Beomsoo Park
Seunghwan Ji
Denoising Diffusion Probabilistic Models (NeurIPS 2020)
Denoising Diffusion Implicit Models (ICLR 2021)
42023.05.10Donggeun Sean KoDiffusion Models Beat GANs in Image Synthesis (NeurIPS 2021)
Zero-Shot Text-to-Image Generation (ICML 2021)
52023.05.17Namkyeong Cho
Sangwoo Jo
High-Resolution Image Synthesis with Latent Diffusion Models (CVPR 2022)
DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation (CVPR 2023)
62023.05.24Kwangsu Mun
Jisu Kim
An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion (ICLR 2023)
Adding Conditional Control to Text-to-Image Diffusion Models (ICCV 2023)
72023.05.31Beomsoo Park
Seunghwan Ji
LoRA: Low-Rank Adaptation of Large Language Models (ICLR 2022)
Multi-Concept Customization of Text-to-Image Diffusion (CVPR 2023)
82023.08.30Donggeun Sean Ko
Sangwoo Jo
Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding (NeurIPS 2022)
Imagen Editor and EditBench: Advancing and Evaluating Text-Guided Image Inpainting (CVPR 2023)
92023.09.06SeonHoon Kim
Seunghwan Ji
Hierarchical Text-Conditional Image Generation with CLIP Latents
SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equations (ICLR 2022)
102023.09.13Namkyeong Cho
Junhyoung Lee
DeepFloyd IF
SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis (ICLR 2024 Spotlight)
112023.09.20HyoungSeo Cho
Sangwoo Jo
HyperDreamBooth: HyperNetworks for Fast Personalization of Text-to-Image Models (CVPR 2024)
T2I-Adapter: Learning Adapters to Dig out More Controllable Ability for Text-to-Image Diffusion Models (AAAI 2024)
122023.09.27Sehwan Park
Junhyoung Lee
GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models (PMLR 2022)
Scaling Autoregressive Multi-Modal Models: Pretraining and Instruction Tuning
132023.10.11Jeonghwa Yoo
SeonHoon Kim
Synthetic Data from Diffusion Models Improves ImageNet Classification (TMLR 2023)
Your Diffusion Model is Secretly a Zero-Shot Classifier (ICCV 2023)
142023.10.18Seunghwan JiA Study on the Evaluation of Generative Models
152023.10.25Sangwoo Jo
HyoungSeo Cho
Progressive Distillation for Fast Sampling of Diffusion Models (ICLR 2022 Spotlight)
ConceptLab: Creative Generation using Diffusion Prior Constraints (ACM Transactions on Graphics 2024)
162023.11.01SeonHoon Kim
Jeonghwa Yoo
BBDM: Image-to-image Translation with Brownian Bridge Diffusion Models (CVPR 2023)
Make-A-Video: Text-to-Video Generation without Text-Video Data (ICLR 2023)
172023.11.15Sehwan Park
Junhyoung Lee
Diffusion Models already have a Semantic Latent Space (ICLR 2023)
Align your Latents: High-Resolution Video Synthesis with Latent Diffusion Models (CVPR 2023)
182023.11.29Donggeun Sean KoVideo Diffusion Models (NeurIPS 2022)
192024.03.13Geonhak SongAnimate Anyone: Consistent and Controllable Image-to-Video Synthesis for Character Animation (CVPR Workshop 2023)
DreaMoving: A Human Video Generation Framework based on Diffusion Models (CVPR Workshop 2023)
202024.03.20Junhyoung LeeMuse: Text-To-Image Generation via Masked Generative Transformers (ICML 2023)
212024.03.27Seunghwan JiScaling up GANs for Text-to-Image Synthesis (CVPR 2023)
222024.04.03Sangwoo JoConsistency Models (ICML 2023)
232024.04.24Donghyun HanLatent Consistency Models: Synthesizing High-Resolution Images with Few-Step Inference
242024.05.01Jeonghwa YooDreamPose: Fashion Image-to-Video Synthesis via Stable Diffusion (ICCV 2023)
252024.05.08Sehwan ParkLLM-grounded Diffusion: Enhancing Prompt Understanding of Text-to-Image Diffusion Models with Large Language Models (TMLR 2024)
262024.05.15Kyeongmin YuAnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning (ICLR 2024 Spotlight)
272024.05.22Jeongin LeeNeRF: Representing Scenes as Neural Radiance Fields for View Synthesis (ECCV 2020 Oral)
282024.05.29Hyunsoo Kim3D Gaussian Splatting for Real-Time Radiance Field Rendering (SIGGRAPH 2023)
292024.06.12Donggeun Sean KoDiffInject: Revisiting Debias via Synthetic Data Generation using Diffusion-based Style Injection (CVPR Workshop 2024)
302024.06.26Jeonghwa Yoo
Kyeongmin Yu
Point-E: A System for Generating 3D Point Clouds from Complex Prompts
Shap-E: Generating Conditional 3D Implicit Function
312024.07.03Geonhak SongDreamFusion: Text-to-3D using 2D Diffusion (ICLR 2023)
322024.07.17Sangwoo Jo
Junhyoung Lee
Magic3D: High-Resolution Text-to-3D Content Creation (CVPR 2023)
Scalable Diffusion Models with Transformers (ICCV 2023)
332024.07.24Jeongin Lee
Hyunsoo Kim
DreamBooth3D: Subject-Driven Text-to-3D Generation (ICCV 2023)
Style Aligned Image Generation via Shared Attention (CVPR 2024)
342024.09.18Sangwoo JoOne-step Image Translation with Text-to-Image Models
352024.09.25Joongwon LeeOne-step Diffusion with Distribution Matching Distillation (CVPR 2024)
362024.10.02Donghyun HanLCM-LoRA: A Universal Stable-Diffusion Acceleration Module
372024.10.09Kyeongmin YuIP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Models
382024.10.30Jeongin LeeZero-1-to-3: Zero-shot One Image to 3D Object (ICCV 2023)
392024.11.06Geonhak SongMVDream: Multi-view Diffusion for 3D Generation (ICLR 2024)
402024.11.13Kyeongmin YuProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillation (NeurIPS 2023)
412024.11.27Jeonghwa Yoo
Sangwoo Jo
One-2-3-45: Any Single Image to 3D Mesh in 45 Seconds without Per-Shape Optimization (NeurIPS 2023)
Zero123++: a Single Image to Consistent Multi-view Diffusion Base Model
422024.12.04Joongwon Lee
Donghyun Han
LRM: Large Reconstruction Model for Single Image to 3D (ICLR 2024 Oral)
LGM: Large Multi-View Gaussian Model for High-Resolution 3D Content Creation (ECCV 2024 Oral)
432024.12.11Kyeongmin YuDreamGaussian: Generative Gaussian Splatting for Efficient 3D Content Creation (ICLR 2024 Oral)
442024.12.18Geonhak Song
Donggeun Sean Ko
CAT3D: Create Anything in 3D with Multi-View Diffusion Models (NeurIPS 2024 Oral)
Coin3D: Controllable and Interactive 3D Assets Generation with Proxy-Guided Conditioning (CVPR Workshop 2024)

Jupyter Book Update Procedure

  1. Clone the repo on your local computer
git clone https://github.com/Pseudo-Lab/text-to-image-generation.git
  1. Install required packages
pip install jupyter-book==0.15.1
pip install ghp-import==2.1.0
  1. Change the contents in book/docs folder with the following format and update _toc.yml file accordingly

  • 3.1. Add information section on top of the markdown page
- **Title:** {논문 제목}, {학회/학술지명}

- **Reference**
    - Paper:  [{논문 링크}]({논문 링크})
    - Code: [{code 링크}]({code 링크})
    - Review: [{review 링크}]({review 링크})
    
- **Author:** {리뷰 작성자 기입}

- **Edited by:** {리뷰 편집자 기입}

- **Last updated on {최종 update 날짜 e.g. Apr. 12, 2023}**
  • 3-2. Use the following template when displaying images
:::{figure-md} 
<img src="{주소}" alt="{tag명}" class="bg-primary mb-1" width="{800px}">

{제목} \  (source: {출처})
:::
  • 3-3. Update _toc.yml file accordingly
format: jb-book
root: intro
parts:
- caption: Paper/Code Review
  chapters:
  - file: docs/review/vae
  - file: docs/review/gan
  1. Build the book using Jupyter Book command
jupyter-book build ./book
  1. Sync your local and remote repositories
cd pseudodiffusers
git add .
git commit -m "adding my first book!"
git push
  1. Publish your Jupyter Book with Github Pages
ghp-import -n -p -f book/_build/html -m "initial publishing"
3d-generation
diffusion
image-generation
research
video-generation

Contributors

jasonjo97

153 commits

seanko29

33 commits

egshkim

28 commits

innimu

22 commits

Languages

HTML

93.7%

CSS

2.9%

JavaScript

2.5%