This is an official pytorch implementation of “Bottom-Up Human Pose Estimation by Ranking Heatmap-Guided Adaptive Keypoint Estimates” (https://arxiv.org/abs/2006.15480).

Object detection with multi-level representations generated from deep high-resolution representation learning (HRNetV2h). This is an official implementation for our TPAMI paper "Deep High-Resolution Representation Learning for Visual Recognition".https://arxiv.org/abs/1908.07919

The OCR approach is rephrased as Segmentation Transformer:https://arxiv.org/abs/1909.11065. This is an official implementation of semantic segmentation for HRNet.https://arxiv.org/abs/1908.07919

[ NeurIPS2021] This is an official implementation of our paper "HRFormer: High-Resolution Transformer for Dense Prediction".

This is an official implementation of facial landmark detection for our TPAMI paper "Deep High-Resolution Representation Learning for Visual Recognition".https://arxiv.org/abs/1908.07919

This is an official pytorch implementation of Lite-HRNet: A Lightweight High-Resolution Network.

This is an official implementation of our CVPR 2021 paper "Bottom-Up Human Pose Estimation Via Disentangled Keypoint Regression" (https://arxiv.org/abs/2104.02300)

Train the HRNet model on ImageNet

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

Object detection with multi-level representations generated from deep high-resolution representation learning (HRNetV2h).