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3D Human Pose Estimation On Mpi Inf 3Dhp

評価指標

MPJPE
PCK

評価結果

このベンチマークにおける各モデルのパフォーマンス結果

Paper Title
VNect (Augm.)124.776.6VNect: Real-time 3D Human Pose Estimation with a Single RGB Camera
HMR124.272.9End-to-end Recovery of Human Shape and Pose
Single-Shot Multi-Person122.275.2Single-Shot Multi-Person 3D Pose Estimation From Monocular RGB
Mehta117.675.7Monocular 3D Human Pose Estimation In The Wild Using Improved CNN Supervision
PONet115.076.1PONet: Robust 3D Human Pose Estimation via Learning Orientations Only
DenseRaC114.276.9DenseRaC: Joint 3D Pose and Shape Estimation by Dense Render-and-Compare
Pose Consensus (monocular)112.180.6Consensus-based Optimization for 3D Human Pose Estimation in Camera Coordinates
GeoRep (fully-supervised)110.880.2Weakly-Supervised 3D Human Pose Learning via Multi-view Images in the Wild
XFormer (HRNet)109.8-XFormer: Fast and Accurate Monocular 3D Body Capture
EpipolarPose (fully-supervised)108.9977.5Self-Supervised Learning of 3D Human Pose using Multi-view Geometry
SPIN105.276.4Learning to Reconstruct 3D Human Pose and Shape via Model-fitting in the Loop
DSR104.7-Learning to Regress Bodies from Images using Differentiable Semantic Rendering
CanonPose10477CanonPose: Self-Supervised Monocular 3D Human Pose Estimation in the Wild
RSC-Net103.36-3D Human Shape and Pose from a Single Low-Resolution Image with Self-Supervised Learning
PoseNet3D102.481.9PoseNet3D: Learning Temporally Consistent 3D Human Pose via Knowledge Distillation
DynaBOA101.579.5Out-of-Domain Human Mesh Reconstruction via Dynamic Bilevel Online Adaptation
EvoSkeleton99.781.2Cascaded deep monocular 3D human pose estimation with evolutionary training data
XNect (SelecSLS)98.482.8XNect: Real-time Multi-Person 3D Motion Capture with a Single RGB Camera
DDT97.8-DiffMesh: A Motion-aware Diffusion Framework for Human Mesh Recovery from Videos
RepNet (3DHP)97.882.5RepNet: Weakly Supervised Training of an Adversarial Reprojection Network for 3D Human Pose Estimation
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3D Human Pose Estimation On Mpi Inf 3Dhp | SOTA | HyperAI超神経