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 291300 of 665 papers

TitleStatusHype
BlanketGen - A synthetic blanket occlusion augmentation pipeline for MoCap datasets0
3D-UGCN: A Unified Graph Convolutional Network for Robust 3D Human Pose Estimation from Monocular RGB Images0
Embodied Scene-aware Human Pose Estimation0
Monocular Human Pose and Shape Reconstruction using Part Differentiable Rendering0
BioPose: Biomechanically-accurate 3D Pose Estimation from Monocular Videos0
Lightweight Multi-View 3D Pose Estimation through Camera-Disentangled Representation0
Maximum-Margin Structured Learning with Deep Networks for 3D Human Pose Estimation0
Beyond Weak Perspective for Monocular 3D Human Pose Estimation0
3D Pictorial Structures for Multiple Human Pose Estimation0
Benchmarking 3D Human Pose Estimation Models Under Occlusions0
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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