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 331340 of 665 papers

TitleStatusHype
PoseGraphNet++: Enriching 3D Human Pose with Orientation Estimation0
Unsupervised 3D Pose Estimation with Non-Rigid Structure-from-Motion Modeling0
Iterative Graph Filtering Network for 3D Human Pose EstimationCode0
Weakly Supervised Multi-Modal 3D Human Body Pose Estimation for Autonomous Driving0
ActionPrompt: Action-Guided 3D Human Pose Estimation With Text and Pose Prompting0
ProxyCap: Real-time Monocular Full-body Capture in World Space via Human-Centric Proxy-to-Motion Learning0
Implicit 3D Human Mesh Recovery using Consistency with Pose and Shape from Unseen-view0
MPM: A Unified 2D-3D Human Pose Representation via Masked Pose Modeling0
Representation learning of vertex heatmaps for 3D human mesh reconstruction from multi-view images0
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