Human volumetric capture is a long-standing topic in computer vision and computer
graphics. Although high-quality results can be achieved using sophisticated off-line systems …

To address the ill-posed problem caused by partial observations in monocular human
volumetric capture, we present AvatarCap, a novel framework that introduces animatable …

Abstract 4D modeling of human-object interactions is critical for numerous applications.
However, efficient volumetric capture and rendering of complex interaction scenarios …

High-quality and complete 4D reconstruction of human activities is critical for immersive
VR/AR experience, but it suffers from inherent self-scanning constraint and consequent …

We present a deep learning-based volumetric capture approach for performance capture
using a passive and highly sparse multi-view capture system. We focus on a template-free …

Convenient 4D modeling of human-object interactions is essential for numerous
applications. However, monocular tracking and rendering of complex interaction scenarios …

We present the first approach to volumetric performance capture and novel-view rendering
at real-time speed from monocular video, eliminating the need for expensive multi-view …

Abstract 4D reconstruction and rendering of human activities is critical for immersive VR/AR
experience. Recent advances still fail to recover fine geometry and texture results with the …

We present TexMesh, a novel approach to reconstruct detailed human meshes with high-
resolution full-body texture from RGB-D video. TexMesh enables high quality free-viewpoint …

Human performance capture is a highly important computer vision problem with many
applications in movie production and virtual/augmented reality. Many previous performance …