SOTAVerified

3D Multi-Person Pose Estimation (absolute)

This task aims to solve absolute 3D multi-person pose Estimation (camera-centric coordinates). No ground truth human bounding box and human root joint coordinates are used during testing stage.

( Image credit: RootNet )

Papers

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Showing 1–10 of 20 papers

TitleStatusHype
Towards Robust and Smooth 3D Multi-Person Pose Estimation from Monocular Videos in the Wild—0
Explicit Occlusion Reasoning for Multi-person 3D Human Pose Estimation—0
Dynamic Graph Reasoning for Multi-person 3D Pose Estimation—0
VirtualPose: Learning Generalizable 3D Human Pose Models from Virtual DataCode1
Dual networks based 3D Multi-Person Pose Estimation from Monocular VideoCode1
Permutation-Invariant Relational Network for Multi-person 3D Pose Estimation—0
Distribution-Aware Single-Stage Models for Multi-Person 3D Pose EstimationCode1
Deep Monocular 3D Human Pose Estimation via Cascaded Dimension-Lifting—0
Monocular 3D Multi-Person Pose Estimation by Integrating Top-Down and Bottom-Up NetworksCode1
Graph and Temporal Convolutional Networks for 3D Multi-person Pose Estimation in Monocular VideosCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Depth Prediction NetworkMPJPE292—Unverified
2Depth Prediction NetworkMPJPE120—Unverified
3VirtualPose3DPCK44—Unverified