ClimateNeRF: Extreme Weather Synthesis in Neural Radiance Field
This enables people to visualize climate change impacts in their own environments, though it is incremental as it combines existing techniques.
The authors tackled the problem of synthesizing realistic extreme weather effects in 3D scenes by fusing physical simulations with neural radiance fields (NeRF), resulting in ClimateNeRF, which produces significantly more realistic weather renderings like smog, snow, and floods compared to state-of-the-art 2D and 3D methods.
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.