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 51–75 of 665 papers

TitleStatusHype
Depth-based Privileged Information for Boosting 3D Human Pose Estimation on RGB—0
SPiKE: 3D Human Pose from Point Cloud SequencesCode1
Multi-view Pose Fusion for Occlusion-Aware 3D Human Pose EstimationCode0
PoseMamba: Monocular 3D Human Pose Estimation with Bidirectional Global-Local Spatio-Temporal State Space ModelCode2
Pose Magic: Efficient and Temporally Consistent Human Pose Estimation with a Hybrid Mamba-GCN Network—0
Analyzing Data Efficiency and Performance of Machine Learning Algorithms for Assessing Low Back Pain Physical Rehabilitation Exercises—0
Flexible graph convolutional network for 3D human pose estimationCode0
3D-UGCN: A Unified Graph Convolutional Network for Robust 3D Human Pose Estimation from Monocular RGB Images—0
ESCAPE: Energy-based Selective Adaptive Correction for Out-of-distribution 3D Human Pose Estimation—0
RT-Pose: A 4D Radar Tensor-based 3D Human Pose Estimation and Localization Benchmark—0
PAFUSE: Part-based Diffusion for 3D Whole-Body Pose EstimationCode1
STGFormer: Spatio-Temporal GraphFormer for 3D Human Pose Estimation in Video—0
RTMW: Real-Time Multi-Person 2D and 3D Whole-body Pose EstimationCode0
Markerless Multi-view 3D Human Pose Estimation: a survey—0
Graph and Skipped Transformer: Exploiting Spatial and Temporal Modeling Capacities for Efficient 3D Human Pose Estimation—0
MeshPose: Unifying DensePose and 3D Body Mesh reconstructionCode1
KITRO: Refining Human Mesh by 2D Clues and Kinematic-tree RotationCode1
Occlusion Handling in 3D Human Pose Estimation with Perturbed Positional Encoding—0
Di^2Pose: Discrete Diffusion Model for Occluded 3D Human Pose Estimation—0
RemoCap: Disentangled Representation Learning for Motion Capture—0
FinePOSE: Fine-Grained Prompt-Driven 3D Human Pose Estimation via Diffusion ModelsCode2
Pose Priors from Language Models—0
Multi-hop graph transformer network for 3D human pose estimation—0
Probablistic Restoration with Adaptive Noise Sampling for 3D Human Pose EstimationCode0
Behavior Imitation for Manipulator Control and Grasping with Deep Reinforcement Learning—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