high-resolution-net

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 paperhttps//arxiv.org/abs/1908.07919

Image Classification uses a blend of C++ and Python for efficient preprocessing of image datasets. This setup helps organize images into pixel folders and generates text files for object counts, streamlining the classification process. 🖼️📂