Abstract We present Non-Rigid Neural Radiance Fields (NR-NeRF), a reconstruction and
novel view synthesis approach for general non-rigid dynamic scenes. Our approach takes …

Abstract We present Multi-Garment Network (MGN), a method to predict body shape and
clothing, layered on top of the SMPL model from a few frames (1-8) of a video. Several …

This paper describes how to obtain accurate 3D body models and texture of arbitrary people
from a single, monocular video in which a person is moving. Based on a parametric body …

While the ready availability of 3D scan data has influenced research throughout computer
vision, less attention has focused on 4D data; that is 3D scans of moving non-rigid objects …

We present a novel method for high detail-preserving human avatar creation from
monocular video. A parameterized body model is refined and optimized to maximally …

We present Octopus, a learning-based model to infer the personalized 3D shape of people
from a few frames (1-8) of a monocular video in which the person is moving with a …

High-fidelity clothing reconstruction is the key to achieving photorealism in a wide range of
applications including human digitization, virtual try-on, etc. Recent advances in learning …

Animals are widespread in nature and the analysis of their shape and motion is important in
many fields and industries. Modeling 3D animal shape, however, is difficult because the 3D …

We present a system that builds 3D models of non-rigidly moving surfaces from scratch in
real time using a single RGB-D stream. Our solution is based on the variational level set …

The increasing demand for 3D content in augmented and virtual reality has motivated the
development of volumetric performance capture systemsnsuch as the Light Stage. Recent …