The project is an official implementation of our CVPR2019 paper "Deep High-Resolution Representation Learning for Human Pose Estimation"
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Updated
Aug 30, 2024 - Cuda
The project is an official implementation of our CVPR2019 paper "Deep High-Resolution Representation Learning for Human Pose Estimation"
The project is an official implement of our ECCV2018 paper "Simple Baselines for Human Pose Estimation and Tracking(https://arxiv.org/abs/1804.06208)"
Fast and accurate human pose estimation in PyTorch. Contains implementation of "Real-time 2D Multi-Person Pose Estimation on CPU: Lightweight OpenPose" paper.
A PyTorch toolkit for 2D Human Pose Estimation.
Distribution-Aware Coordinate Representation for Human Pose Estimation
Official pytorch Code for CVPR2019 paper "Fast Human Pose Estimation" https://arxiv.org/abs/1811.05419
TensorFlow implementation of "Simple Baselines for Human Pose Estimation and Tracking", ECCV 2018
Official TensorFlow implementation of "PoseFix: Model-agnostic General Human Pose Refinement Network", CVPR 2019
Multi-person Human Pose Estimation with HigherHRNet in Pytorch, with TensorRT support
Simple Baselines for Human Pose Estimation and Tracking
[IJCAI 2022] Code for the paper "Dite-HRNet: Dynamic Lightweight High-Resolution Network for Human Pose Estimation"
[IEEE TMM] Code for the paper "HRNeXt: High-Resolution Context Network for Crowd Pose Estimation"
The project is an official implement of our ACM Multimedia 2019 paper "Fast Non-Local Neural Networks with Spectral Residual Learning"
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