The project is an official implementation of our CVPR2019 paper "Deep High-Resolution Representation Learning for Human Pose Estimation"

[ICLR2025, ICML2025, NeurIPS2025 Spotlight] Quantized Attention achieves speedup of 2-5x compared to FlashAttention, without losing end-to-end metrics across language, image, and video models.

Distribution-Aware Coordinate Representation for Human Pose Estimation

Official pytorch Code for CVPR2019 paper "Fast Human Pose Estimation" https://arxiv.org/abs/1811.05419

[ECCV'2022 Oral] PyTorch implementation for: SimCC: a Simple Coordinate Classification Perspective for Human Pose Estimation (http://arxiv.org/abs/2107.03332). Old name: SimDR

This repo is copied from https://github.com/leoxiaobin/deep-high-resolution-net.pytorch

Implementation for : TokenPose: Learning Keypoint Tokens for Human Pose Estimation （https://arxiv.org/abs/2104.03516）. Accepted by ICCV 2021.

Res2Net for Pose Estimation using Simple Baselines as the baseline

Pose Estimation using Swin-Transformer based on DARK Pose.