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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.