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
SMAP: Single-Shot Multi-Person Absolute 3D Pose EstimationCode1
HMOR: Hierarchical Multi-Person Ordinal Relations for Monocular Multi-Person 3D Pose Estimation—0
HDNet: Human Depth Estimation for Multi-Person Camera-Space LocalizationCode1
Multi-Person Absolute 3D Human Pose Estimation with Weak Depth SupervisionCode1
Camera Distance-aware Top-down Approach for 3D Multi-person Pose Estimation from a Single RGB ImageCode0
LCR-Net++: Multi-person 2D and 3D Pose Detection in Natural Images—0
RNN-DBSCAN: A Density-Based Clustering Algorithm Using Reverse Nearest Neighbor Density EstimatesCode0
Single-Shot Multi-Person 3D Pose Estimation From Monocular RGBCode0
LCR-Net: Localization-Classification-Regression for Human Pose—0
Towards 3D Human Pose Estimation in the Wild: a Weakly-supervised ApproachCode0
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Benchmark Results

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