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
Deep Learning-Based Human Pose Estimation: A SurveyCode1
Graph and Temporal Convolutional Networks for 3D Multi-person Pose Estimation in Monocular VideosCode1
Invariant Teacher and Equivariant Student for Unsupervised 3D Human Pose EstimationCode1
End-to-End Human Pose and Mesh Reconstruction with TransformersCode1
CanonPose: Self-Supervised Monocular 3D Human Pose Estimation in the WildCode1
Accurate 3D Hand Pose Estimation for Whole-Body 3D Human Mesh EstimationCode1
Beyond Static Features for Temporally Consistent 3D Human Pose and Shape from a VideoCode1
Residual Pose: A Decoupled Approach for Depth-based 3D Human Pose EstimationCode1
Temporal Smoothing for 3D Human Pose Estimation and Localization for Occluded PeopleCode1
AdaFuse: Adaptive Multiview Fusion for Accurate Human Pose Estimation in the WildCode1
Synthetic Training for Accurate 3D Human Pose and Shape Estimation in the WildCode1
SMAP: Single-Shot Multi-Person Absolute 3D Pose EstimationCode1
Pose2Mesh: Graph Convolutional Network for 3D Human Pose and Mesh Recovery from a 2D Human PoseCode1
Monocular Expressive Body Regression through Body-Driven AttentionCode1
Weakly Supervised Generative Network for Multiple 3D Human Pose HypothesesCode1
I2L-MeshNet: Image-to-Lixel Prediction Network for Accurate 3D Human Pose and Mesh Estimation from a Single RGB ImageCode1
3D Human Motion Estimation via Motion Compression and RefinementCode1
Perceiving 3D Human-Object Spatial Arrangements from a Single Image in the WildCode1
3D Human Shape and Pose from a Single Low-Resolution Image with Self-Supervised LearningCode1
Combining Implicit Function Learning and Parametric Models for 3D Human ReconstructionCode1
SIZER: A Dataset and Model for Parsing 3D Clothing and Learning Size Sensitive 3D ClothingCode1
Multi-person 3D Pose Estimation in Crowded Scenes Based on Multi-View GeometryCode1
SRNet: Improving Generalization in 3D Human Pose Estimation with a Split-and-Recombine ApproachCode1
Self-supervision on Unlabelled OR Data for Multi-person 2D/3D Human Pose EstimationCode1
MeTRAbs: Metric-Scale Truncation-Robust Heatmaps for Absolute 3D Human Pose EstimationCode1
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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