Awesome Person Re-identification

High-performance multiple object tracking based on YOLO, Deep SORT, and KLT 🚀

跨平台的视频结构化（视频分析）框架，觉得有帮助的请给个星星 : ) 。**VideoPipe下一版本正在开发中，在保证跨平台、易上手的前提下，预计性能直逼deepstream等各硬件平台官方框架**。

Out-of-the-box code and models for CMU's object detection and tracking system for multi-camera surveillance videos. Speed optimized Faster-RCNN model. Tensorflow based. Also supports EfficientDet. WACVW'20

EANet: Enhancing Alignment for Cross-Domain Person Re-identification

CVPR2018: Unsupervised Cross-dataset Person Re-identification by Transfer Learning of Spatio-temporal Patterns

TNNLS'22 🗽 Parameter-Efficient Person Re-identification in the 3D Space 🗽

Implementing RepNet(a two-stream multitask learning network) to do vehicle Re-identification, vehicle search(or vehicle match) with PyTorch 可用于车辆细粒度识别，车辆再识别，车辆匹配，车辆检索，RepNet/MDNet的一种PyTorch实现

TCSVT2018 Pedestrian Alignment Network for Large-scale Person Re-identification

Simple pytorch unofficial implement of paper: Learning Discriminative Features with Multiple Granularities for Person Re-Identification

Official implementation for "CLIP-ReID: Exploiting Vision-Language Model for Image Re-identification without Concrete Text Labels" (AAAI 2023)

[ECCV 2020] QAConv: Interpretable and Generalizable Person Re-Identification with Query-Adaptive Convolution and Temporal Lifting, and [CVPR 2022] GS: Graph Sampling Based Deep Metric Learning

Simple model to Track and Re-identify individuals in different cameras/videos.(Yolov3 & Yolov4)

A Pytorch Implementation of "Unlabeled Samples Generated by GAN Improve the Person Re-identification Baseline in vitro"(ICCV17)

VehicleX: Simulating Content Consistent Vehicle Datasets with Attribute Descent (ECCV 2020, TPAMI 2023)

This is Top 3 Code for the Person ReID Compitition of NAIC

Awesome Cross-modality Person Re-identification

Awesome Vehicle Re-identification

vehicle re-identification baseline for veri and vehicleID dataset

A strong baseline for body part-based person re-identification (check out our WACV23 paper)