Popular GitHub Repositories for Person Reidentification

OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimation

Object Detection toolkit based on PaddlePaddle. It supports object detection, instance segmentation, multiple object tracking and real-time multi-person keypoint detection.

Real-Time and Accurate Full-Body Multi-Person Pose Estimation&Tracking System

Gluon CV Toolkit

Code repo for realtime multi-person pose estimation in CVPR'17 (Oral)

Torchreid: Deep learning person re-identification in PyTorch.

OpenBot leverages smartphones as brains for low-cost robots. We have designed a small electric vehicle that costs about $50 and serves as a robot body. Our software stack for Android smartphones supports advanced robotics workloads such as person following and real-time autonomous navigation.

Base on YOLOv5 Head Person Helmet Detection on Construction Sites，基于目标检测工地安全帽和禁入危险区域识别系统，??附 YOLOv5 训练自己的数据集超详细教程??2021.3新增可视化界面❗❗

一人公司 AI 工具系列，长期更新，帮助大家提升工作效率，开启一人公司! One-Person Company AI Tools Series – continuously updated to help boost productivity and empower your solo business!

Fast and accurate human pose estimation in PyTorch. Contains implementation of "Real-time 2D Multi-Person Pose Estimation on CPU: Lightweight OpenPose" paper.

Open-Source AI Camera. Empower any camera/CCTV with state-of-the-art AI, including facial recognition, person recognition(RE-ID) car detection, fall detection and more

Monocular, One-stage, Regression of Multiple 3D People and their 3D positions & trajectories in camera & global coordinates. ROMP[ICCV21], BEV[CVPR22], TRACE[CVPR2023]

:couple: Joint Discriminative and Generative Learning for Person Re-identification. CVPR'19 (Oral) :couple:

Awesome Person Re-identification

:dancer: Real-time single person pose estimation for Android and iOS.

We present MocapNET, a real-time method that estimates the 3D human pose directly in the popular Bio Vision Hierarchy (BVH) format, given estimations of the 2D body joints originating from monocular color images. Our contributions include: (a) A novel and compact 2D pose NSRM representation. (b) A human body orientation classifier and an ensemble of orientation-tuned neural networks that regress the 3D human pose by also allowing for the decomposition of the body to an upper and lower kinematic hierarchy. This permits the recovery of the human pose even in the case of significant occlusions. (c) An efficient Inverse Kinematics solver that refines the neural-network-based solution providing 3D human pose estimations that are consistent with the limb sizes of a target person (if known). All the above yield a 33% accuracy improvement on the

Official PyTorch implementation of "Camera Distance-aware Top-down Approach for 3D Multi-person Pose Estimation from a Single RGB Image", ICCV 2019

Keras version of Realtime Multi-Person Pose Estimation project

Random Erasing Data Augmentation. Experiments on CIFAR10, CIFAR100 and Fashion-MNIST

[Pedestron] Generalizable Pedestrian Detection: The Elephant In The Room. @ CVPR2021