Neural Shadow Mapping
Graphics
2023-01-16 v1
Abstract
We present a neural extension of basic shadow mapping for fast, high quality hard and soft shadows. We compare favorably to fast pre-filtering shadow mapping, all while producing visual results on par with ray traced hard and soft shadows. We show that combining memory bandwidth-aware architecture specialization and careful temporal-window training leads to a fast, compact and easy-to-train neural shadowing method. Our technique is memory bandwidth conscious, eliminates the need for post-process temporal anti-aliasing or denoising, and supports scenes with dynamic view, emitters and geometry while remaining robust to unseen objects.
Keywords
Cite
@article{arxiv.2301.05262,
title = {Neural Shadow Mapping},
author = {Sayantan Datta and Derek Nowrouzezahrai and Christoph Schied and Zhao Dong},
journal= {arXiv preprint arXiv:2301.05262},
year = {2023}
}
Comments
Project Page: https://sayan1an.github.io/neuralShadowMapping.html