pose
Real-time 3D multi-person pose estimation demo in PyTorch. OpenVINO backend can be used for fast inference on CPU.
Simple Pose: Rethinking and Improving a Bottom-up Approach for Multi-Person Pose Estimation
Dataset of the paper "Cross-View Tracking for Multi-Human 3D Pose Estimation at over 100 FPS"
Code for "Fast and Robust Multi-Person 3D Pose Estimation from Multiple Views" (CVPR 2019, T-PAMI 2021)
Camera calibration & 3D pose estimation tools for AcinoSet
Implementation of the GCPR19 Paper "Iterative Greedy Matching for 3D Human Pose Tracking from Multiple Views"
Self-Supervised Learning of 3D Human Pose using Multi-view Geometry (CVPR2019)
The project is an official implement of our ECCV2018 paper "Simple Baselines for Human Pose Estimation and Tracking(https://arxiv.org/abs/1804.06208)"
Implementation of "Joint Training of a Convolutional Network and a Graphical Model for Human Pose Estimation"
NeurIPS-2021: Direct Multi-view Multi-person 3D Human Pose Estimation
Cascaded Pyramid Network for Multi-Person Pose Estimation (CVPR 2018)
Official code of "HybrIK: A Hybrid Analytical-Neural Inverse Kinematics Solution for 3D Human Pose and Shape Estimation", CVPR 2021
OpenMMLab Pose Estimation Toolbox and Benchmark.
[ICCV 2023] PyTorch Implementation of "MotionBERT: A Unified Perspective on Learning Human Motion Representations"
KAPAO is an efficient single-stage human pose estimation model that detects keypoints and poses as objects and fuses the detections to predict human poses.
Fully Convolutional Networks for End-to-End Multi-Person Pose Estimation
Source code of the paper Scene-Aware 3D Multi-Human Motion Capture, EUROGRAPHICS 2023
The official repo for [NeurIPS'22] "ViTPose: Simple Vision Transformer Baselines for Human Pose Estimation" and [TPAMI'23] "ViTPose++: Vision Transformer for Generic Body Pose Estimation"
Transforms for video datasets in pytorch
regresses camera pose from image pairs based on method presented in https://arxiv.org/pdf/1702.01381.pdf
CVPR 2022 - Official code repository for the paper: Accurate 3D Body Shape Regression using Metric and Semantic Attributes.
Multi-Person 3D Pose and Shape Estimation via Inverse Kinematics and Refinement
Official Pytorch implementation of "Pose2Mesh: Graph Convolutional Network for 3D Human Pose and Mesh Recovery from a 2D Human Pose", ECCV 2020