[HN Gopher] Instant neural graphics primitives with a multiresol... ___________________________________________________________________ Instant neural graphics primitives with a multiresolution hash encoding Author : ath92 Score : 61 points Date : 2022-01-16 20:35 UTC (2 hours ago) (HTM) web link (nvlabs.github.io) (TXT) w3m dump (nvlabs.github.io) | WithinReason wrote: | Goodbye polygons, hello neural networks? | aappleby wrote: | More like "run this low-quality polygon and raytracing renderer | at 320x240 @20 fps, upscale to 4k120 with acceptable quality". | aantix wrote: | I've seen the GTA demo. | | Are there any commercial games currently doing this? | JayStavis wrote: | Neural rendering? I doubt it. Check out deep learning super | sampling though (DLSS) from NVIDIA, which has to be plumbed | into the game itself to enable. | | https://www.nvidia.com/en-us/geforce/technologies/dlss/ | The_rationalist wrote: | ath92 wrote: | For some additional context, when the original NeRF paper | (https://arxiv.org/pdf/2003.08934.pdf) was published 2 years ago, | it reportedly took at least 12 hours (depending on hardware used | of course) to train on the scene with the bulldozer. This has now | been reduced to about 5 seconds (!), with realtime rendering of | the result. | hwers wrote: | The gigapixel example could be done with fourier features which | takes about a few minutes to train (on colab-like resources). | Definitely still a huge improvement though (and based on more | clever hashing techniques than optimization). | [deleted] ___________________________________________________________________ (page generated 2022-01-16 23:00 UTC)