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Found 7 papers, 4 papers with code
EMDB: The Electromagnetic Database of Global 3D Human Pose and Shape in the Wild
EMDB is a novel dataset that contains high-quality 3D SMPL pose and shape parameters with global body and camera trajectories for in-the-wild videos.
Hi4D: 4D Instance Segmentation of Close Human Interaction
We propose Hi4D, a method and dataset for the automatic analysis of physically close human-human interaction under prolonged contact.
X-Avatar: Expressive Human Avatars
Our method models bodies, hands, facial expressions and appearance in a holistic fashion and can be learned from either full 3D scans or RGB-D data.
Vid2Avatar: 3D Avatar Reconstruction from Videos in the Wild via Self-supervised Scene Decomposition
Specifically, we define a temporally consistent human representation in canonical space and formulate a global optimization over the background model, the canonical human shape and texture, and per-frame human pose parameters.
PINA: Learning a Personalized Implicit Neural Avatar from a Single RGB-D Video Sequence
We present a novel method to learn Personalized Implicit Neural Avatars (PINA) from a short RGB-D sequence.
Human Performance Capture from Monocular Video in the Wild
In this work, we propose a method capable of capturing the dynamic 3D human shape from a monocular video featuring challenging body poses, without any additional input.
Shape-aware Multi-Person Pose Estimation from Multi-View Images
In this paper we contribute a simple yet effective approach for estimating 3D poses of multiple people from multi-view images.
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3D Multi-Person Pose Estimation
Multi-Person Pose Estimation
