Shypd.aiThe largest open index of AI toolsDeep-high-resolution-net.pytorch is an open-source implementation of the CVPR2019 paper "Deep High-Resolution Representation Learning for Human Pose Estimation." It provides models and code for human pose estimation on COCO and MPII datasets.
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Deep-high-resolution-net.pytorch is an official PyTorch implementation of the research paper "Deep High-Resolution Representation Learning for Human Pose Estimation" presented at CVPR 2019. This project focuses on maintaining high-resolution representations throughout the entire process of human pose estimation, unlike many existing methods that recover high-resolution data from low-resolution outputs. The network achieves this by starting with a high-resolution subnetwork and gradually adding parallel multi-resolution subnetworks, performing repeated multi-scale fusions. This approach leads to more accurate and spatially precise keypoint heatmaps. The repository includes code, pretrained models, and instructions for training and testing on benchmark datasets like COCO and MPII, making it a valuable resource for researchers and developers in computer vision.
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