Title
Deep relightable textures: volumetric performance capture with neural rendering
Abstract
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 advances are pushing free viewpoint relightable videos of dynamic human performances closer to photorealistic quality. However, despite significant efforts, these sophisticated systems are limited by reconstruction and rendering algorithms which do not fully model complex 3D structures and higher order light transport effects such as global illumination and sub-surface scattering. In this paper, we propose a system that combines traditional geometric pipelines with a neural rendering scheme to generate photorealistic renderings of dynamic performances under desired viewpoint and lighting. Our system leverages deep neural networks that model the classical rendering process to learn implicit features that represent the view-dependent appearance of the subject independent of the geometry layout, allowing for generalization to unseen subject poses and even novel subject identity. Detailed experiments and comparisons demonstrate the efficacy and versatility of our method to generate high-quality results, significantly outperforming the existing state-of-the-art solutions.
Year
DOI
Venue
2020
10.1145/3414685.3417814
ACM Transactions on Graphics
Keywords
DocType
Volume
neural rendering,novel view synthesis,reflectance estimation,relighting,volumetric capture
Journal
39
Issue
ISSN
Citations 
6
0730-0301
0
PageRank 
References 
Authors
0.34
0
19
Name
Order
Citations
PageRank
Abhimitra Meka1193.02
Rohit Pandey2222.64
Christian Hane328117.03
Sergio Orts-Escolano431329.45
Peter Barnum500.34
Philip L. Davidson6663.70
Daniel Erickson7121.64
Yinda Zhang835024.48
Jonathan Taylor933414.52
Sofien Bouaziz1093435.79
Chloe LeGendre11203.87
Wan-Chun Ma1236222.64
Ryan S. Overbeck131658.54
Thabo Beeler1463930.77
Paul Debevec154955449.10
Shahram Izadi165573285.39
Christian Theobalt173211159.16
C. Rhemann18124046.56
Sean Ryan Fanello1938021.80