A new technology called Neural Radiance Field involves training artificial intelligence algorithms for allow the creation of 3D objects from two-dimensional photosand now there is also a NVIDIA’s NeRF.
NeRF artificial intelligence has the ability to fill in the blanks, so to speak, by interpolating what 2D photos have not captured, this is a neat trick that could lead to advancements in various fields, such as video games and autonomous driving, but now there is NVIDIA’s NeRF, developed with a new NeRF techniquethe fastest to date, says the companywhich takes only seconds to train and generate a 3D object.
It only takes a few seconds to train the model, called Instant NeRFusing dozens of photos and the camera angles from which they were taken, after which it is able to generate a 3D scene in just “tens of milliseconds”, resulting even 1000 times faster than its competitors.
Like other NVIDIA NeRF techniques, it requires images taken from multiple locations, and for photos with multiple subjects, photos taken without too much movement are preferred, otherwise the result would be blurry.
The evolution of NVIDIA’s NeRF to date
NVIDIA explains that early NeRF models don’t take too long to produce results, in fact it does just a few minutes to render of a 3D scene, even if the subject in some images is obstructed by things, such as pillars and furniture, nevertheless training them took hours.
There NeRF version of NVIDIA requires just a few seconds for trainingbecause it is based on a technique developed by the company called multi-resolution hash grid coding, which is optimized to run efficiently on its GPUs, and can also run on a single GPU, although it is faster on cards with core tensors that provide a performance increase for artificial intelligence.
The company believes the Instant NeRF it could be used to train robots and to help autonomous driving systems understand the dimensions and shapes of real-world objects. NVIDIA also sees a future for technology in entertainment and architecture, where it can be used to generate 3D models of real environments that creators can modify during the planning process.
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