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 501525 of 665 papers

TitleStatusHype
3D Human Pose Estimation using Spatio-Temporal Networks with Explicit Occlusion Training0
Predicting Camera Viewpoint Improves Cross-dataset Generalization for 3D Human Pose Estimation0
Lightweight Multi-View 3D Pose Estimation through Camera-Disentangled Representation0
Monocular Human Pose and Shape Reconstruction using Part Differentiable Rendering0
Weakly Supervised 3D Human Pose and Shape Reconstruction with Normalizing Flows0
Weakly-Supervised 3D Human Pose Learning via Multi-view Images in the Wild0
Back to the Future: Joint Aware Temporal Deep Learning 3D Human Pose EstimationCode0
3D Human Pose Estimation via Explicit Compositional Depth Maps0
AnimePose: Multi-person 3D pose estimation and animation0
Lightweight 3D Human Pose Estimation Network Training Using Teacher-Student Learning0
Learning 3D Human Shape and Pose from Dense Body PartsCode0
ActiveMoCap: Optimized Viewpoint Selection for Active Human Motion CaptureCode0
Multi-task Deep Learning for Real-Time 3D Human Pose Estimation and Action RecognitionCode0
DeepFuse: An IMU-Aware Network for Real-Time 3D Human Pose Estimation from Multi-View Image0
Consensus-based Optimization for 3D Human Pose Estimation in Camera CoordinatesCode0
Single-shot 3D multi-person pose estimation in complex images0
Chirality Nets for Human Pose RegressionCode0
HEMlets Pose: Learning Part-Centric Heatmap Triplets for Accurate 3D Human Pose Estimation0
PoseLifter: Absolute 3D human pose lifting network from a single noisy 2D human poseCode0
On Boosting Single-Frame 3D Human Pose Estimation via Monocular Videos0
Not All Parts Are Created Equal: 3D Pose Estimation by Modeling Bi-Directional Dependencies of Body Parts0
Exploiting Spatial-Temporal Relationships for 3D Pose Estimation via Graph Convolutional NetworksCode0
Occlusion-Aware Networks for 3D Human Pose Estimation in Video0
Optimizing Network Structure for 3D Human Pose Estimation0
DenseRaC: Joint 3D Pose and Shape Estimation by Dense Render-and-Compare0
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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