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 576600 of 665 papers

TitleStatusHype
Neural Body Fitting: Unifying Deep Learning and Model-Based Human Pose and Shape EstimationCode0
3D-CODED : 3D Correspondences by Deep DeformationCode0
Learning from Synthetic HumansCode0
3D Human Pose Estimation in RGBD Images for Robotic Task LearningCode0
Self-Supervised 3D Human Pose Estimation with Multiple-View GeometryCode0
Learning 3D Human Shape and Pose from Dense Body PartsCode0
NToP: NeRF-Powered Large-scale Dataset Generation for 2D and 3D Human Pose Estimation in Top-View Fisheye ImagesCode0
Self-Supervised Learning of 3D Human Pose using Multi-view GeometryCode0
Learning 3D Human Pose from Structure and MotionCode0
Self-supervised Learning of Motion CaptureCode0
A Comprehensive Study of Weight Sharing in Graph Networks for 3D Human Pose EstimationCode0
Convolutional Mesh Regression for Single-Image Human Shape ReconstructionCode0
V2V-PoseNet: Voxel-to-Voxel Prediction Network for Accurate 3D Hand and Human Pose Estimation from a Single Depth MapCode0
ConvFormer: Parameter Reduction in Transformer Models for 3D Human Pose Estimation by Leveraging Dynamic Multi-Headed Convolutional AttentionCode0
PoseLifter: Absolute 3D human pose lifting network from a single noisy 2D human poseCode0
Consensus-based Optimization for 3D Human Pose Estimation in Camera CoordinatesCode0
Learning 3D Human Dynamics from VideoCode0
VarGes: Improving Variation in Co-Speech 3D Gesture Generation via StyleCLIPSCode0
Joint 3D Human Shape Recovery and Pose Estimation from a Single Image with Bilayer GraphCode0
Unite the People: Closing the Loop Between 3D and 2D Human RepresentationsCode0
Towards 3D Human Pose Estimation in the Wild: a Weakly-supervised ApproachCode0
Iterative Graph Filtering Network for 3D Human Pose EstimationCode0
Single-Shot Multi-Person 3D Pose Estimation From Monocular RGBCode0
Optimizing Local-Global Dependencies for Accurate 3D Human Pose EstimationCode0
Computer Vision to the Rescue: Infant Postural Symmetry Estimation from Incongruent AnnotationsCode0
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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