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 176200 of 665 papers

TitleStatusHype
Regular Splitting Graph Network for 3D Human Pose EstimationCode0
TAPE: Temporal Attention-based Probabilistic human pose and shape EstimationCode0
Interweaved Graph and Attention Network for 3D Human Pose EstimationCode1
Occlusion Robust 3D Human Pose Estimation with StridedPoseGraphFormer and Data Augmentation0
Sampling is Matter: Point-guided 3D Human Mesh ReconstructionCode1
Human Pose Estimation in Monocular Omnidirectional Top-View Images0
HybrIK-X: Hybrid Analytical-Neural Inverse Kinematics for Whole-body Mesh RecoveryCode3
Monocular 3D Human Pose Estimation for Sports Broadcasts using Partial Sports Field RegistrationCode1
Self-supervised 3D Human Pose Estimation from a Single Image0
ConvFormer: Parameter Reduction in Transformer Models for 3D Human Pose Estimation by Leveraging Dynamic Multi-Headed Convolutional AttentionCode0
SportsPose -- A Dynamic 3D sports pose datasetCode1
3D Human Pose Estimation via Intuitive Physics0
PoseFormerV2: Exploring Frequency Domain for Efficient and Robust 3D Human Pose EstimationCode2
Global Adaptation meets Local Generalization: Unsupervised Domain Adaptation for 3D Human Pose EstimationCode1
One-Stage 3D Whole-Body Mesh Recovery with Component Aware TransformerCode2
Global-to-Local Modeling for Video-based 3D Human Pose and Shape EstimationCode1
Zolly: Zoom Focal Length Correctly for Perspective-Distorted Human Mesh ReconstructionCode1
A Hybrid ANN-SNN Architecture for Low-Power and Low-Latency Visual PerceptionCode1
DiffMesh: A Motion-aware Diffusion Framework for Human Mesh Recovery from Videos0
POTTER: Pooling Attention Transformer for Efficient Human Mesh RecoveryCode1
BoPR: Body-aware Part Regressor for Human Shape and Pose EstimationCode0
3D Human Mesh Estimation from Virtual MarkersCode2
Diffusion-Based 3D Human Pose Estimation with Multi-Hypothesis AggregationCode1
Highly Efficient 3D Human Pose Tracking from Events with Spiking Spatiotemporal TransformerCode1
PSVT: End-to-End Multi-person 3D Pose and Shape Estimation with Progressive Video Transformers0
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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