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 171180 of 665 papers

TitleStatusHype
Humans in 4D: Reconstructing and Tracking Humans with TransformersCode3
Decomposed Human Motion Prior for Video Pose Estimation via Adversarial Training0
XFormer: Fast and Accurate Monocular 3D Body Capture0
NIKI: Neural Inverse Kinematics with Invertible Neural Networks for 3D Human Pose and Shape EstimationCode2
HuManiFlow: Ancestor-Conditioned Normalising Flows on SO(3) Manifolds for Human Pose and Shape Distribution EstimationCode1
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
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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