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 11–20 of 20 papers

TitleStatusHype
Dynamic Graph Reasoning for Multi-person 3D Pose Estimation—0
Explicit Occlusion Reasoning for Multi-person 3D Human Pose Estimation—0
HMOR: Hierarchical Multi-Person Ordinal Relations for Monocular Multi-Person 3D Pose Estimation—0
LCR-Net: Localization-Classification-Regression for Human Pose—0
Permutation-Invariant Relational Network for Multi-person 3D Pose Estimation—0
Towards Robust and Smooth 3D Multi-Person Pose Estimation from Monocular Videos in the Wild—0
RNN-DBSCAN: A Density-Based Clustering Algorithm Using Reverse Nearest Neighbor Density EstimatesCode0
Towards 3D Human Pose Estimation in the Wild: a Weakly-supervised ApproachCode0
Camera Distance-aware Top-down Approach for 3D Multi-person Pose Estimation from a Single RGB ImageCode0
Single-Shot Multi-Person 3D Pose Estimation From Monocular RGBCode0
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Benchmark Results

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