👫 Joint Discriminative and Generative Learning for Person Re-identification. CVPR'19 (Oral) 👫
TNNLS'22 🗽 Parameter-Efficient Person Re-identification in the 3D Space 🗽
State-of-the-art model for person re-identification in Multi-camera Multi-Target Tracking. Benchmarked on Market-1501 and DukeMTMTC-reID datasets.
A strong implementation of PCB (Beyond Part Models), outperforming all existing implementations.
Joint Disentangling and Adaptation for Cross-Domain Person Re-Identification. ECCV'20 (Oral)
ReID + SFDA - Dual-Region Augmentation (Foreground Noise + Background Shuffle) for robust person re-identification (ReID) and source-free domain adaptation (SFDA).
A graphical user interface for labeling DukeMTMC-ReID
Repo for BMVC2020 paper "BCaR: Beginner Classifier as Regularization Towards Generalizable Re-ID"
Person Re-ID system: ResNet-50 IBN-a + BNNeck trained on Market-1501 (Rank-1 81.80%, mAP 60.38%). FAISS gallery search, cross-dataset eval on DukeMTMC-reID, YOLOv8 video demo with persistent global IDs. Pure PyTorch, Colab T4 + Apple M1 MPS.
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