"NVIDIA researchers have successfully trained a neural network to find these jagged edges and perform high-quality anti-aliasing by determining the best color for each pixel, and then apply proper colors to create smoother edges and improve image quality. This technique is known as Deep Learning Super Sample (DLSS). DLSS is like an “Ultra AA” mode-- it provides the highest quality anti-aliasing with fewer artifacts than other types of anti-aliasing.
DLSS requires a training set of full resolution frames of the aliased images that use one sample per pixel to act as a baseline for training. Another full resolution set of frames with at least 64 samples per pixel acts as the reference that DLSS aims to achieve."
https://developer.nvidia.com/rtx/ngx
At first I thought of sample as it is used in graphics, an intersection of channel and a pixel. But that really doesn't make any sense in this context, going from 1 channel to 64 channels ?
So I am thinking it is sample as in the statistics term but I don't understand how a static image could come up with 64 variations to compare to? Even going from FHD to 4K UHD is only 4 times the amount of pixels. Trying to parse that second paragraph I really can't make any sense of it.
