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 4150 of 665 papers

TitleStatusHype
PyMAF-X: Towards Well-aligned Full-body Model Regression from Monocular ImagesCode2
MotionAGFormer: Enhancing 3D Human Pose Estimation with a Transformer-GCNFormer NetworkCode2
Attention Mechanism Exploits Temporal Contexts: Real-Time 3D Human Pose ReconstructionCode1
PyMAF: 3D Human Pose and Shape Regression with Pyramidal Mesh Alignment Feedback LoopCode1
AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent ConversationCode1
3D Human Motion Estimation via Motion Compression and RefinementCode1
Cyclic Test-Time Adaptation on Monocular Video for 3D Human Mesh ReconstructionCode1
D&D: Learning Human Dynamics from Dynamic CameraCode1
ARTS: Semi-Analytical Regressor using Disentangled Skeletal Representations for Human Mesh Recovery from VideosCode1
3D Human Mesh Regression with Dense CorrespondenceCode1
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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