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SOTA Re-identification Methods and Toolbox

v1.3.0

2 years ago

Features & Improvements

New Features

  • Vision Transformer backbone, see config in configs/Market1501/bagtricks_vit.yml
  • Self-Distillation with EMA update
  • Gradient Clip

Improvements

  • Faster dataloader with pre-fetch thread and cuda stream
  • Impl freezebackbone function in step of optimizer
  • Optimize DDP training speed by removing find_unused_parameters in DDP

v1.0.0

3 years ago

Features & Improvements:

v0.1.1

3 years ago

Some major features:

  • Distributed DataParallel(DDP) training and evaluation.

  • Model distillation.

  • Caffe/ONNX/TensoRT deployment.

  • Pretrained model release.

v0.1

3 years ago

Some major features:

  • High modular design.

  • SoTA results on conventional person re-id, cross-domain person re-id, partial person re-id, and vehicle re-id.

  • multi-GPU training and multi-dataset testing simultaneously

  • standard dataset splits used by the most paper.

  • visualization methods including rank list and annotation visualization.

  • abundant evaluation metrics including CMC, mAP, mINP, and ROC.