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 1–10 of 665 papers

TitleStatusHype
Systematic Comparison of Projection Methods for Monocular 3D Human Pose Estimation on Fisheye Images—0
ExtPose: Robust and Coherent Pose Estimation by Extending ViTs—0
PoseGRAF: Geometric-Reinforced Adaptive Fusion for Monocular 3D Human Pose EstimationCode0
Learning Pyramid-structured Long-range Dependencies for 3D Human Pose EstimationCode0
UPTor: Unified 3D Human Pose Dynamics and Trajectory Prediction for Human-Robot Interaction—0
PoseBench3D: A Cross-Dataset Analysis Framework for 3D Human Pose EstimationCode1
HDiffTG: A Lightweight Hybrid Diffusion-Transformer-GCN Architecture for 3D Human Pose EstimationCode0
Continuous Normalizing Flows for Uncertainty-Aware Human Pose Estimation—0
3D Human Pose Estimation via Spatial Graph Order Attention and Temporal Body Aware TransformerCode0
Unsupervised Cross-Domain 3D Human Pose Estimation via Pseudo-Label-Guided Global Transforms—0
Show:102550
← PrevPage 1 of 67Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SMPLifyMean Reconstruction Error (mm)79.9—Unverified
2SMPLify (dense)Mean Reconstruction Error (mm)74.5—Unverified
3Wang et al.Mean Reconstruction Error (mm)71.3—Unverified
4OursMean Reconstruction Error (mm)64—Unverified
5Simo-Serra et al.Mean Reconstruction Error (mm)56.7—Unverified
6DSRFMean Reconstruction Error (mm)40.3—Unverified
7TGPMean Reconstruction Error (mm)39.1—Unverified
8Dual-source approachMean Reconstruction Error (mm)38.9—Unverified
9DMHSR(J,B,D)Mean Reconstruction Error (mm)33.7—Unverified
10Recurrent 3D Pose Sequence MachinesMean Reconstruction Error (mm)30.8—Unverified