Google researchers have revealed their updated NeRF-W (Neural Radiance Fields in the Wild) algorithm, which basically creates detailed 3D models of locations around the world by using the reference data from 2D tourists’ photos. This algorithm can also remove unwanted objects and normalize the lighting conditions so they look as natural as possible. Nerf-W is applied to internet photo collections of famous landmarks and the resulting 3D models are even more photo-realistic than in the actual images. Read more for a video and additional information.
Technically speaking, NeRF-W disentangles the shared, underlying 3D geometry from transient objects and photometric variations, thus generating a consistent, photo-realistic scene representation that can be rendered from novel viewpoints. This means that the 3D models are even cleaner and filled with less noise than the neural renderings of the past.
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NeRF-W captures lighting and photometric post-processing in a low-dimensional latent embedding space. Interpolating between two embeddings smoothly captures variation in appearance without affecting 3D geometry,” said the research team.