market-1501

⛹ Pytorch ReID: A tiny, friendly, strong pytorch implement of person re-id / vehicle re-id baseline. Tutorial 👉https://github.com/layumi/Person_reID_baseline_pytorch/tree/master/tutorial

👫 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)

👗3D Magic Mirror: Clothing Reconstruction from a Single Image via a Causal Perspective👗 Single-View 3D Reconstruction

Multi-Tracking Multi-Camera Person Re-Identification

In this assignment, we explored the use of neural networks to solve two common computer vision tasks using the PyTorch framework. We had given a video-surveillance dataset containing images of multiple persons each of which was captured multiple times by different cameras along with a set of annotations that specify attributes of each person such as age, gender and clothing.

Multi-Object Tracking Using FCOS + DeepSORT

person re-identification using deep learning