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 551–575 of 665 papers

TitleStatusHype
On Boosting Single-Frame 3D Human Pose Estimation via Monocular Videos—0
Online Test-time Adaptation for 3D Human Pose Estimation: A Practical Perspective with Estimated 2D Poses—0
On the role of depth predictions for 3D human pose estimation—0
On Triangulation as a Form of Self-Supervision for 3D Human Pose Estimation—0
Optimising 2D Pose Representation: Improve Accuracy, Stability and Generalisability Within Unsupervised 2D-3D Human Pose Estimation—0
Optimizing Network Structure for 3D Human Pose Estimation—0
PandaNet: Anchor-Based Single-Shot Multi-Person 3D Pose Estimation—0
PandaNet : Anchor-Based Single-Shot Multi-Person 3D Pose Estimation—0
Patch-based 3D Human Pose Refinement—0
PC-HMR: Pose Calibration for 3D Human Mesh Recovery from 2D Images/Videos—0
Picture: A Probabilistic Programming Language for Scene Perception—0
LiCamPose: Combining Multi-View LiDAR and RGB Cameras for Robust Single-frame 3D Human Pose Estimation—0
PONet: Robust 3D Human Pose Estimation via Learning Orientations Only—0
Pose-Conditioned Joint Angle Limits for 3D Human Pose Reconstruction—0
PoseGraphNet++: Enriching 3D Human Pose with Orientation Estimation—0
PoseGU: 3D Human Pose Estimation with Novel Human Pose Generator and Unbiased Learning—0
PoseIRM: Enhance 3D Human Pose Estimation on Unseen Camera Settings via Invariant Risk Minimization—0
Pose-Oriented Transformer with Uncertainty-Guided Refinement for 2D-to-3D Human Pose Estimation—0
Pose Priors from Language Models—0
PoseRN: A 2D pose refinement network for bias-free multi-view 3D human pose estimation—0
PostoMETRO: Pose Token Enhanced Mesh Transformer for Robust 3D Human Mesh Recovery—0
Predicting Camera Viewpoint Improves Cross-dataset Generalization for 3D Human Pose Estimation—0
Predicting people’s 3D poses from short sequences—0
Proactive Multi-Camera Collaboration For 3D Human Pose Estimation—0
Probabilistic 3D Human Shape and Pose Estimation from Multiple Unconstrained Images in the Wild—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