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 with no code
Improving Real-Time Omnidirectional 3D Multi-Person Human Pose Estimation with People Matching and Unsupervised 2D-3D Lifting
Therefore, this paper presents one of the first 3D multi-person human pose estimation systems that is able to work in real-time and is also able to handle basic forms of occlusion.
MUG: Multi-human Graph Network for 3D Mesh Reconstruction from 2D Pose
Our method works like the following: First, to model the multi-human environment, it processes multi-human 2D poses and builds a novel heterogeneous graph, where nodes from different people and within one person are connected to capture inter-human interactions and draw the body geometry (i. e., skeleton and mesh structure).
Single-shot 3D multi-person pose estimation in complex images
In this paper, we propose a new single shot method for multi-person 3D human pose estimation in complex images.
Multi-Person 3D Human Pose Estimation from Monocular Images
Multi-person 3D human pose estimation from a single image is a challenging problem, especially for in-the-wild settings due to the lack of 3D annotated data.
