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 361370 of 665 papers

TitleStatusHype
Learning Local Recurrent Models for Human Mesh Recovery0
Human Pose Regression with Residual Log-likelihood EstimationCode1
Conditional Directed Graph Convolution for 3D Human Pose EstimationCode1
Everybody Is Unique: Towards Unbiased Human Mesh Recovery0
PoseRN: A 2D pose refinement network for bias-free multi-view 3D human pose estimation0
Real-Time Multi-View 3D Human Pose Estimation using Semantic Feedback to Smart Edge SensorsCode1
Motion Projection Consistency Based 3D Human Pose Estimation with Virtual Bones from Monocular Videos0
Part-Aware Measurement for Robust Multi-View Multi-Human 3D Pose Estimation and TrackingCode1
Intelligent Carpet: Inferring 3D Human Pose From Tactile Signals0
THUNDR: Transformer-based 3D HUmaN Reconstruction with Markers0
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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