1. Hrnet Semantic SegmentationThe 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
2. Hrnet Maskrcnn BenchmarkObject detection with multi-level representations generated from deep high-resolution representation learning (HRNetV2h).
3. Hrnet Bottom Up Pose EstimationThis is an official pytorch implementation of “Bottom-Up Human Pose Estimation by Ranking Heatmap-Guided Adaptive Keypoint Estimates” (https://arxiv.org/abs/2006.15480).
4. Higherhrnet Human Pose EstimationThis is an official implementation of our CVPR 2020 paper "HigherHRNet: Scale-Aware Representation Learning for Bottom-Up Human Pose Estimation" (https://arxiv.org/abs/1908.10357)
5. Hrnet Facial Landmark DetectionThis 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
8. HRFormerThis is an official implementation of our NeurIPS 2021 paper "HRFormer: High-Resolution Transformer for Dense Prediction".
9. Lite-HRNetThis is an official pytorch implementation of Lite-HRNet: A Lightweight High-Resolution Network.