3D Multi-Person Human Pose Estimation
4 papers with code • 0 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in 3D Multi-Person Human Pose Estimation
UNIPD-BPE
Latest papers
Part-Aware Measurement for Robust Multi-View Multi-Human 3D Pose Estimation and Tracking
ivclab/Part-Aware_Measurement_for_3D_Pose_Estimation_and_Tracking
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This paper introduces an approach for multi-human 3D pose estimation and tracking based on calibrated multi-view.
Learning to Estimate Robust 3D Human Mesh from In-the-Wild Crowded Scenes
hongsukchoi/3dcrowdnet_release
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CVPR 2022
Second, we propose a joint-based regressor that distinguishes a target person's feature from others.
Multi-person 3D Pose Estimation in Crowded Scenes Based on Multi-View Geometry
HeCraneChen/3D-Crowd-Pose-Estimation-Based-on-MVG
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ECCV 2020
In this paper, we depart from the multi-person 3D pose estimation formulation, and instead reformulate it as crowd pose estimation.
XNect: Real-time Multi-Person 3D Motion Capture with a Single RGB Camera
rwightman/pytorch-image-models
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The first stage is a convolutional neural network (CNN) that estimates 2D and 3D pose features along with identity assignments for all visible joints of all individuals. We contribute a new architecture for this CNN, called SelecSLS Net, that uses novel selective long and short range skip connections to improve the information flow allowing for a drastically faster network without compromising accuracy.
