Re:Neural Supersampling for Real-Time Rendering
by carrolldunham on Saturday July 04, 2020 @01:34AM
(#23730366)
Right - so a single low-res image should not be paired with the high-res one and labelled as input and output, because that implies the algorithm turned the one data into the other, which it did not do.
Re:Neural Supersampling for Real-Time Rendering
by pseudosavant on Saturday July 04, 2020 @02:53PM
(#23734156)
This isn't about upsampling low-res bitmaps. It is a technique for upsampling the output of a game engine.
The low-res image is itself output generated from a lot of other input the game engine generates. That same input that is already being generated anyway can also be fed into this to improve the post-processing. Finding ways to productively reuse already existing/generated data is the hallmark of any top (graphically) game.
I read a detailed write-up on the graphics pipeline for GTA:V on Xbox 360. It blew my mind how many different ways they reused every single bit that ever hit the RAM. Which explains how they pulled off those graphics on a system with half as much RAM as an Apple Watch.
It uses color, depth and subpixel motion vectors of 1-4 previous frames. All things that modern game engines can easily calculate. You didn't even need to read the paper to get this info, it's literally in a picture on the blog post.