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 276–300 of 665 papers

TitleStatusHype
Bring Your Rear Cameras for Egocentric 3D Human Pose Estimation—0
EVOPOSE: A Recursive Transformer For 3D Human Pose Estimation With Kinematic Structure Priors—0
Everybody Is Unique: Towards Unbiased Human Mesh Recovery—0
3D Human Pose Estimation on a Configurable Bed from a Pressure Image—0
Learning Unorthogonalized Matrices for Rotation Estimation—0
Lightweight 3D Human Pose Estimation Network Training Using Teacher-Student Learning—0
Estimating Egocentric 3D Human Pose in the Wild with External Weak Supervision—0
ESCAPE: Energy-based Selective Adaptive Correction for Out-of-distribution 3D Human Pose Estimation—0
3D Human Pose Estimation in the Wild by Adversarial Learning—0
Error Bounds of Projection Models in Weakly Supervised 3D Human Pose Estimation—0
Enhanced 3D Human Pose Estimation from Videos by using Attention-Based Neural Network with Dilated Convolutions—0
BlazePose GHUM Holistic: Real-time 3D Human Landmarks and Pose Estimation—0
2D-3D Pose Consistency-based Conditional Random Fields for 3D Human Pose Estimation—0
A Bayesian Framework for Sparse Representation-Based 3D Human Pose Estimation—0
End-to-end Dynamic Matching Network for Multi-view Multi-person 3d Pose Estimation—0
BlanketGen - A synthetic blanket occlusion augmentation pipeline for MoCap datasets—0
3D-UGCN: A Unified Graph Convolutional Network for Robust 3D Human Pose Estimation from Monocular RGB Images—0
Embodied Scene-aware Human Pose Estimation—0
Monocular Human Pose and Shape Reconstruction using Part Differentiable Rendering—0
BioPose: Biomechanically-accurate 3D Pose Estimation from Monocular Videos—0
Lightweight Multi-View 3D Pose Estimation through Camera-Disentangled Representation—0
Maximum-Margin Structured Learning with Deep Networks for 3D Human Pose Estimation—0
Beyond Weak Perspective for Monocular 3D Human Pose Estimation—0
3D Pictorial Structures for Multiple Human Pose Estimation—0
Benchmarking 3D Human Pose Estimation Models Under Occlusions—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