mks0601/3DMPPE_POSENET_RELEASE
PyTorch implementation of a deep learning model that estimates 3D human body joint positions from single RGB images.
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This repository provides the official PyTorch implementation of a 2019 ICCV paper on camera distance-aware top-down 3D multi-person pose estimation. The model uses deep learning to detect and estimate 3D positions of human joints (skeleton keypoints) from a single RGB image. It supports multiple benchmark datasets including Human3.6M, MPII, MS COCO 2017, MuCo-3DHP, and MuPoTS-3D, and includes visualization utilities for pose estimation results.
Frequently asked
- What is mks0601/3DMPPE_POSENET_RELEASE?
- PyTorch implementation of a deep learning model that estimates 3D human body joint positions from single RGB images.
- Is 3DMPPE_POSENET_RELEASE open source?
- Yes — mks0601/3DMPPE_POSENET_RELEASE is open source, released under the MIT license.
- What language is 3DMPPE_POSENET_RELEASE written in?
- mks0601/3DMPPE_POSENET_RELEASE is primarily written in Python.
- How popular is 3DMPPE_POSENET_RELEASE?
- mks0601/3DMPPE_POSENET_RELEASE has 864 stars on GitHub.
- Where can I find 3DMPPE_POSENET_RELEASE?
- mks0601/3DMPPE_POSENET_RELEASE is on GitHub at https://github.com/mks0601/3DMPPE_POSENET_RELEASE.