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 351360 of 665 papers

TitleStatusHype
Learning from Synthetic HumansCode0
Cross View Fusion for 3D Human Pose EstimationCode0
Adapted Human Pose: Monocular 3D Human Pose Estimation with Zero Real 3D Pose DataCode0
Learning Pyramid-structured Long-range Dependencies for 3D Human Pose EstimationCode0
Learning Skeletal Graph Neural Networks for Hard 3D Pose EstimationCode0
Learning Temporal 3D Human Pose Estimation with Pseudo-LabelsCode0
Learning to Fuse 2D and 3D Image Cues for Monocular Body Pose EstimationCode0
Decanus to Legatus: Synthetic training for 2D-3D human pose liftingCode0
Lifting from the Deep: Convolutional 3D Pose Estimation from a Single ImageCode0
Multi-person 3D pose estimation from a single image captured by a fisheye camera0
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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