The project is an official implementation of our CVPR2019 paper "Deep High-Resolution Representation Learning for Human Pose Estimation"
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
Train the HRNet model on ImageNet
This is an official pytorch implementation of Lite-HRNet: A Lightweight High-Resolution Network.
tensorflow implementation for "High-Resolution Representations for Labeling Pixels and Regions"
[IJCAI 2022] Code for the paper "Dite-HRNet: Dynamic Lightweight High-Resolution Network for Human Pose Estimation"
Official project website for the AAAI 2022 paper "Stereo Neural Vernier Caliper"
[IEEE TMM] Code for the paper "HRNeXt: High-Resolution Context Network for Crowd Pose Estimation"
HRNetV2 OCR for Tensorflow2
Human pose estimation based on HRNet
Implementation of a Deep High Resolution Network architecture for Face Landmark detection. From the paper:https://arxiv.org/abs/1908.07919
Add a description, image, and links to the high-resolution-net topic page so that developers can more easily learn about it.
To associate your repository with the high-resolution-net topic, visit your repo's landing page and select "manage topics."