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

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Showing 451–475 of 665 papers

TitleStatusHype
Self-Supervised 3D Human Pose Estimation in Static Video Via Neural Rendering—0
Self-Supervised 3D Human Pose Estimation via Part Guided Novel Image Synthesis—0
Self-Supervised Multi-View Synchronization Learning for 3D Pose Estimation—0
Semantic Estimation of 3D Body Shape and Pose using Minimal Cameras—0
Semantics-aware Test-time Adaptation for 3D Human Pose Estimation—0
Shape-Aware Human Pose and Shape Reconstruction Using Multi-View Images—0
Sim2real transfer learning for 3D human pose estimation: motion to the rescue—0
SimPoE: Simulated Character Control for 3D Human Pose Estimation—0
Skeleton Transformer Networks: 3D Human Pose and Skinned Mesh from Single RGB Image—0
Skeletor: Skeletal Transformers for Robust Body-Pose Estimation—0
SkelFormer: Markerless 3D Pose and Shape Estimation using Skeletal Transformers—0
SMPLy Benchmarking 3D Human Pose Estimation in the Wild—0
Sparse Inertial Poser: Automatic 3D Human Pose Estimation from Sparse IMUs—0
Sparse Representation for 3D Shape Estimation: A Convex Relaxation Approach—0
Spatial-Temporal Parallel Transformer for Arm-Hand Dynamic Estimation—0
SPGNet: Spatial Projection Guided 3D Human Pose Estimation in Low Dimensional Space—0
SSP-Net: Scalable Sequential Pyramid Networks for Real-Time 3D Human Pose Regression—0
STGFormer: Spatio-Temporal GraphFormer for 3D Human Pose Estimation in Video—0
Generalizable Human Pose Triangulation—0
Structured Prediction of 3D Human Pose with Deep Neural Networks—0
SVMAC: Unsupervised 3D Human Pose Estimation from a Single Image with Single-view-multi-angle Consistency—0
Systematic Comparison of Projection Methods for Monocular 3D Human Pose Estimation on Fisheye Images—0
"Teaching Independent Parts Separately" (TIPSy-GAN) : Improving Accuracy and Stability in Unsupervised Adversarial 2D to 3D Pose Estimation—0
TEMPO: Efficient Multi-View Pose Estimation, Tracking, and Forecasting—0
Temporal-Aware Refinement for Video-based Human Pose and Shape Recovery—0
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All datasets3DPWMPI-INF-3DHPHuman3.6MHumanEva-IH3WBTotal CaptureEMDBAGORAPanopticSurreal3D Poses in the Wild ChallengeAIST++

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Simple-baselinePA-MPJPE157—Unverified
2HMRMPJPE130—Unverified
3BMPMPVPE119.3—Unverified
4SPINMPVPE116.4—Unverified
5Wenshuo et a;.MPVPE112.6—Unverified
6TCMR (T=16 w/o 3DPW)MPVPE111.5—Unverified
7CHOMPMPVPE110.1—Unverified
8PC-HMRMPVPE108.6—Unverified
93DCrowdNetMPVPE108.5—Unverified
10SMPLifyPA-MPJPE106.8—Unverified
#ModelMetricClaimedVerifiedStatus
1VNect (Augm.)MPJPE124.7—Unverified
2HMRMPJPE124.2—Unverified
3Single-Shot Multi-PersonMPJPE122.2—Unverified
4MehtaMPJPE117.6—Unverified
5PONetMPJPE115—Unverified
6Pose Consensus (monocular)MPJPE112.1—Unverified
7GeoRep (fully-supervised)MPJPE110.8—Unverified
8XFormer (HRNet)MPJPE109.8—Unverified
9EpipolarPose (fully-supervised)MPJPE108.99—Unverified
10SPINMPJPE105.2—Unverified