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Found 4 papers, 2 papers with code
AiOS: All-in-One-Stage Expressive Human Pose and Shape Estimation
Expressive human pose and shape estimation (a. k. a.
WHAC: World-grounded Humans and Cameras
In this study, we aim to recover expressive parametric human models (i. e., SMPL-X) and corresponding camera poses jointly, by leveraging the synergy between three critical players: the world, the human, and the camera.
Learning Dense UV Completion for Human Mesh Recovery
Our method utilizes a dense correspondence map to separate visible human features and completes human features on a structured UV map dense human with an attention-based feature completion module.
Zolly: Zoom Focal Length Correctly for Perspective-Distorted Human Mesh Reconstruction
As it is hard to calibrate single-view RGB images in the wild, existing 3D human mesh reconstruction (3DHMR) methods either use a constant large focal length or estimate one based on the background environment context, which can not tackle the problem of the torso, limb, hand or face distortion caused by perspective camera projection when the camera is close to the human body.
Ranked #5 on
3D Human Pose Estimation
on 3DPW
