@inproceedings{44d7371bd9a7482eafefcc39fe183200,
title = "ClimateNeRF: Extreme Weather Synthesis in Neural Radiance Field",
abstract = "Physical simulations produce excellent predictions of weather effects. Neural radiance fields produce SOTA scene models. We describe a novel NeRF-editing procedure that can fuse physical simulations with NeRF models of scenes, producing realistic movies of physical phenomena in those scenes. Our application - Climate NeRF - allows people to visualize what climate change outcomes will do to them.ClimateNeRF allows us to render realistic weather effects, including smog, snow, and flood. Results can be controlled with physically meaningful variables like water level. Qualitative and quantitative studies show that our simulated results are significantly more realistic than those from SOTA 2D image editing and SOTA 3D NeRF stylization.",
author = "Yuan Li and Lin, {Zhi Hao} and David Forsyth and Huang, {Jia Bin} and Shenlong Wang",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE/CVF International Conference on Computer Vision, ICCV 2023 ; Conference date: 02-10-2023 Through 06-10-2023",
year = "2023",
doi = "10.1109/ICCV51070.2023.00299",
language = "English (US)",
series = "Proceedings of the IEEE International Conference on Computer Vision",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "3204--3215",
booktitle = "Proceedings - 2023 IEEE/CVF International Conference on Computer Vision, ICCV 2023",
address = "United States",
}