Human Pose Estimation Related Publication
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Updated
Aug 7, 2020
Human Pose Estimation Related Publication
Official Pytorch implementation of "Pose2Mesh: Graph Convolutional Network for 3D Human Pose and Mesh Recovery from a 2D Human Pose", ECCV 2020
Official Pytorch implementation of "Beyond Static Features for Temporally Consistent 3D Human Pose and Shape from a Video", CVPR 2021
Code for ICCV2021 paper SPEC: Seeing People in the Wild with an Estimated Camera
Official Pytorch implementation of "Learning to Estimate Robust 3D Human Mesh from In-the-Wild Crowded Scenes", CVPR 2022
Measure the SMPL body model
Our model BUDDI learns the joint distribution of interacting people
ECCV2020 - Official code repository for the paper : Reconstructing NBA Players
NBA2K Dataset for the ECCV2020 paper : Reconstructing NBA Players
Implementation for "3D human pose, shape and texture from low-resolution images and videos", TPAMI 2021
Official Pytorch implementation for 2020 3DV paper "PLACE: Proximity Learning of Articulation and Contact in 3D Environments" and trained models
[CVPR 2023 Highlight] Official implementation of "NeMo: 3D Neural Motion Fields from Multiple Video Instances of the Same Action"
Official implementation of BodyMAP
"Linear Regression vs. Deep Learning". The source code for a simple but effective baseline method for human body measurement estimation using only height and weight information about the person.
Source code for HumanMeshNet: Polygonal Mesh Recovery of Humans, ICCV 2019 Workshop 3DRW
marker-less human motion capture from RGB videos
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