SOTAVerified

3D Human Pose Estimation

3D Human Pose Estimation is a computer vision task that involves estimating the 3D positions and orientations of body joints and bones from 2D images or videos. The goal is to reconstruct the 3D pose of a person in real-time, which can be used in a variety of applications, such as virtual reality, human-computer interaction, and motion analysis.

Papers

Showing 271280 of 665 papers

TitleStatusHype
End-to-end Recovery of Human Shape and PoseCode0
Monocular Total Capture: Posing Face, Body, and Hands in the WildCode0
Multi-hypothesis 3D human pose estimation metrics favor miscalibrated distributionsCode0
3D Human Pose Estimation in RGBD Images for Robotic Task LearningCode0
MetaPose: Fast 3D Pose from Multiple Views without 3D SupervisionCode0
MHEntropy: Entropy Meets Multiple Hypotheses for Pose and Shape RecoveryCode0
Dual-stream Transformer-GCN Model with Contextualized Representations Learning for Monocular 3D Human Pose EstimationCode0
Learning to Dress 3D People in Generative ClothingCode0
Back to the Future: Joint Aware Temporal Deep Learning 3D Human Pose EstimationCode0
Automatic Labeling of Parkinson’s Disease Gait Videos with Weak SupervisionCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Simple-baselinePA-MPJPE157Unverified
2HMRMPJPE130Unverified
3BMPMPVPE119.3Unverified
4SPINMPVPE116.4Unverified
5Wenshuo et a;.MPVPE112.6Unverified
6TCMR (T=16 w/o 3DPW)MPVPE111.5Unverified
7CHOMPMPVPE110.1Unverified
8PC-HMRMPVPE108.6Unverified
93DCrowdNetMPVPE108.5Unverified
10SMPLifyPA-MPJPE106.8Unverified
#ModelMetricClaimedVerifiedStatus
1VNect (Augm.)MPJPE124.7Unverified
2HMRMPJPE124.2Unverified
3Single-Shot Multi-PersonMPJPE122.2Unverified
4MehtaMPJPE117.6Unverified
5PONetMPJPE115Unverified
6Pose Consensus (monocular)MPJPE112.1Unverified
7GeoRep (fully-supervised)MPJPE110.8Unverified
8XFormer (HRNet)MPJPE109.8Unverified
9EpipolarPose (fully-supervised)MPJPE108.99Unverified
10SPINMPJPE105.2Unverified