ntmkimm/Backend-AI-Challenge

Backend for AIC25

Python

0

71 commits

updated Nov 7, 2025

See the code

README

BUCCI_GANG Team System

System Architecture

This tool matches keyframes to scenes based on text descriptions and context image.

Features

  • CLIP & BEiT3 retrieval: Use OpenCLIP and BEiT3 models to find the most likely objects based on text descriptions.

  • OCR & ASR: Extract on-screen text and spoken words from video keyframes using their timestamps.

  • Object detection: Apply D-FINE and Co-DeTR to detect common (COCO) objects in keyframes.

  • Weighted fusion: Combine and re-rank detection results by balancing feature scores within each keyframe.

  • Search algorithm: Use a temporal model and dynamic programming to re-rank all keyframes across time for better overall accuracy.

Demo

Demo on web

Directory Structure

ArgumentDescription
apiBackend API for System
others folderDirectory containing code for extractinge features and testing algorithms

ntmkimm/Backend-AI-Challenge

Backend for AIC25

Python

0

71 commits

updated Nov 7, 2025

See the code

README

BUCCI_GANG Team System

System Architecture

This tool matches keyframes to scenes based on text descriptions and context image.

Features

  • CLIP & BEiT3 retrieval: Use OpenCLIP and BEiT3 models to find the most likely objects based on text descriptions.

  • OCR & ASR: Extract on-screen text and spoken words from video keyframes using their timestamps.

  • Object detection: Apply D-FINE and Co-DeTR to detect common (COCO) objects in keyframes.

  • Weighted fusion: Combine and re-rank detection results by balancing feature scores within each keyframe.

  • Search algorithm: Use a temporal model and dynamic programming to re-rank all keyframes across time for better overall accuracy.

Demo

Demo on web

Directory Structure

ArgumentDescription
apiBackend API for System
others folderDirectory containing code for extractinge features and testing algorithms