[…] Known as inverse rendering, the process uses AI to approximate how light behaves in the real world, enabling researchers to reconstruct a 3D scene from a handful of 2D images taken at different angles. The NVIDIA Research team has developed an approach that accomplishes this task almost instantly — making it one of the first models of its kind to combine ultra-fast neural network training and rapid rendering.
NVIDIA applied this approach to a popular new technology called neural radiance fields, or NeRF.
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“If traditional 3D representations like polygonal meshes are akin to vector images, NeRFs are like bitmap images: they densely capture the way light radiates from an object or within a scene,”
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Showcased in a session at NVIDIA GTC this week, Instant NeRF could be used to create avatars or scenes for virtual worlds, to capture video conference participants and their environments in 3D, or to reconstruct scenes for 3D digital maps.
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Collecting data to feed a NeRF is a bit like being a red carpet photographer trying to capture a celebrity’s outfit from every angle — the neural network requires a few dozen images taken from multiple positions around the scene, as well as the camera position of each of those shots.
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Instant NeRF, however, cuts rendering time by several orders of magnitude. It relies on a technique developed by NVIDIA called multi-resolution hash grid encoding, which is optimized to run efficiently on NVIDIA GPUs. Using a new input encoding method, researchers can achieve high-quality results using a tiny neural network that runs rapidly.
The model was developed using the NVIDIA CUDA Toolkit and the Tiny CUDA Neural Networks library. Since it’s a lightweight neural network, it can be trained and run on a single NVIDIA GPU — running fastest on cards with NVIDIA Tensor Cores.
The technology could be used to train robots and self-driving cars to understand the size and shape of real-world objects by capturing 2D images or video footage of them. It could also be used in architecture and entertainment to rapidly generate digital representations of real environments that creators can modify and build on.
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Source: NeRF Research Turns 2D Photos Into 3D Scenes | NVIDIA Blog
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