🎩 History-Aware Transformation of ReID Features for Multiple Object Tracking

This is the official PyTorch implementation of our paper:

History-Aware Transformation of ReID Features for Multiple Object Tracking
🎓 Ruopeng Gao, Yuyao Wang, Chunxu Liu, Limin Wang
📧 Primary contact: ruopenggao@gmail.com

🔍 Overview

TL; DR. We propose a plug-and-play History-Aware Transformation algorithm for appearance features (i.e., ReID features). Guided by historical information, we seek a more discriminative subspace for target features in video sequences, enabling better differentiation between different trajectories. Our method significantly enhances the reliability of appearance features, improving the performance of ReID-based MOT trackers.

✏️ Citation

If you think this project is helpful, please feel free to leave a ⭐ and cite our paper:

@article{{HATReID-MOT},
  title={History-aware transformation of reid features for multiple object tracking},
  author={Gao, Ruopeng and Wang, Yuyao and Liu, Chunxu and Wang, Limin},
  journal={arXiv preprint arXiv:2503.12562},
  year={2025}
}