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 431440 of 665 papers

TitleStatusHype
Propagating LSTM: 3D Pose Estimation based on Joint Interdependency0
ProPLIKS: Probablistic 3D human body pose estimation0
PSVT: End-to-End Multi-person 3D Pose and Shape Estimation with Progressive Video Transformers0
Random Tree Walk Toward Instantaneous 3D Human Pose Estimation0
Real-Time Hybrid Mapping of Populated Indoor Scenes using a Low-Cost Monocular UAV0
Real-time, low-cost multi-person 3D pose estimation0
ProxyCap: Real-time Monocular Full-body Capture in World Space via Human-Centric Proxy-to-Motion Learning0
Recent Advances in Monocular 2D and 3D Human Pose Estimation: A Deep Learning Perspective0
Recurrent 3D Pose Sequence Machines0
RemoCap: Disentangled Representation Learning for Motion Capture0
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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