Pytorch implementation of 3D human keypoints estimation models
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Updated
Nov 2, 2023
Pytorch implementation of 3D human keypoints estimation models
Official repository of PAFUSE
Change "Lifting from the Deep: Convolutional 3D Pose Estimation from a Single Image" to video input implementation
[TIP 2022] Boosting Monocular 3D Human Pose Estimation with Part Aware Attention
3D human pose and ground truth viewpoint datasets used in the paper "Optimal Camera Point Selection Toward the Most Preferable View of 3-D Human Pose"
Official implementation of ACCV 2020 paper "3D Human Motion Estimation via Motion Compression and Refinement". (Identical repo to https://github.com/ZhengyiLuo/MEVA, will be kept in sync)
This is a pytorch implementation of method based on Lightweight Multi-View 3D Pose Estimation through Camera-Disentangled Representation applying on human pose estimation tasks using 2-view stereo images.
Estimating 3d Landmarks and displaying them in rviz (Cpu)
Human Pose annotation tool. With this tool it is possible to annotate custom 2D skeletons over images or videos. If 3D skeletons are also available, there is also a 3D visualization.
[AAAI 2024] PoseGen: Learning to Generate 3D Human Pose Datasets with NeRF
A real-time 3d human pose estimation trial.
We introduce a new 3D pose estimator and model designed for runners.
EventEgo3D: 3D Human Motion Capture from Egocentric Event Streams [CVPR'24]
3D Multi-person Pose Estimation in Multi-view Environment using 3D U-Net Transformer Networks
Real-time 3D multi-person pose estimation demo on Jetson TX2 with TensorRT.
A toolbox for processing Total Capture dataset
The testing code for OriNet
[BMVC2021] "TransFusion: Cross-view Fusion with Transformer for 3D Human Pose Estimation"
[CVPR 2023 Highlight] Official implementation of "NeMo: 3D Neural Motion Fields from Multiple Video Instances of the Same Action"
[ICRA 2023] Official implementation of "A generic diffusion-based approach for 3D human pose prediction in the wild".
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