Official implementation of CVPR2020 paper "VIBE: Video Inference for Human Body Pose and Shape Estimation"
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Updated
Mar 24, 2023 - Python
Official implementation of CVPR2020 paper "VIBE: Video Inference for Human Body Pose and Shape Estimation"
Official code of "HybrIK: A Hybrid Analytical-Neural Inverse Kinematics Solution for 3D Human Pose and Shape Estimation", CVPR 2021
We present MocapNET, a real-time method that estimates the 3D human pose directly in the popular Bio Vision Hierarchy (BVH) format, given estimations of the 2D body joints originating from monocular color images. Our contributions include: (a) A novel and compact 2D pose NSRM representation. (b) A human body orientation classifier and an ensembl…
[ICCV 2023] PyTorch Implementation of "MotionBERT: A Unified Perspective on Learning Human Motion Representations"
ExPose - EXpressive POse and Shape rEgression
Self-Supervised Learning of 3D Human Pose using Multi-view Geometry (CVPR2019)
A deep neural network that directly reconstructs the motion of a 3D human skeleton from monocular video [ToG 2020]
The Pytorch implementation for "Semantic Graph Convolutional Networks for 3D Human Pose Regression" (CVPR 2019).
😎Awesome list of papers about 3D body
Official Torch7 implementation of "V2V-PoseNet: Voxel-to-Voxel Prediction Network for Accurate 3D Hand and Human Pose Estimation from a Single Depth Map", CVPR 2018
A simple baseline for 3d human pose estimation in PyTorch.
Code for paper "A2J: Anchor-to-Joint Regression Network for 3D Articulated Pose Estimation from a Single Depth Image". ICCV2019
Official project website for the CVPR 2020 paper (Oral Presentation) "Cascaded deep monocular 3D human pose estimation wth evolutionary training data"
[ECCV 2022] Official implementation of the paper "SmoothNet: A Plug-and-Play Network for Refining Human Poses in Videos"
State-of-the-art methods on monocular 3D pose estimation / 3D mesh recovery
Openposeの2D人間骨格データから3D関節データを生成し、その関節データを出力します。
Official implementation of ACCV 2020 paper "3D Human Motion Estimation via Motion Compression and Refinement" (Identical repo to https://github.com/KlabCMU/MEVA, will be kept in sync)
3D Multi-Person Pose Estimation by Integrating Top-Down and Bottom-Up Networks
The baseline project for inferencing various Pose Estimation tflite models with TFLiteSwift on iOS
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