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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)
This repo is copied from https://github.com/leoxiaobin/deep-high-resolution-net.pytorch
Object detection with multi-level representations generated from deep high-resolution representation learning (HRNetV2h).
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