Deep Learning Super Sampling: Difference between revisions

Revision as of 13:22, 31 January 2025

Revision as of 13:28, 31 January 2025

Line 88:

=== DLSS 2.0 ===

DLSS 2.0 is a [[temporal anti-aliasing]] [[upsampling]] (TAAU) implementation, using data from previous frames extensively through sub-pixel jittering to resolve fine detail and reduce aliasing. The data DLSS 2.0 collects includes: the raw low-resolution input, [[motion vector]]s, [[Z-buffering|depth buffers]], and [[Exposure value|exposure]] / brightness information.<ref name="NVIDIA" /> It can also be used as a simpler TAA implementation where the image is rendered at 100% resolution, rather than being upsampled by DLSS, Nvidia brands this as [[DLAA]] (deepDeep learningLearning antiAnti-aliasingAliasing).<ref name=":4">{{Cite web|date=2021-09-28|title=What is Nvidia DLAA? An Anti-Aliasing Explainer|url=https://www.digitaltrends.com/computing/what-is-nvidia-dlaa/|access-date=2022-02-10|website=Digital Trends|language=en}}</ref>

TAA(U) is used in many modern video games and [[game engine]]s;<ref>[https://de45xmedrsdbp.cloudfront.net/Resources/files/TemporalAA_small-59732822.pdf Temporal AA small] Cloud Front</ref> however, all previous implementations have used some form of manually written [[heuristic]]s to prevent temporal artifacts such as [[Ghosting (television)|ghosting]] and [[Flicker (light)|flickering]]. One example of this is neighborhood clamping which forcefully prevents samples collected in previous frames from deviating too much compared to nearby pixels in newer frames. This helps to identify and fix many temporal artifacts, but deliberately removing fine details in this way is analogous to applying a [[Box blur|blur filter]], and thus the final image can appear blurry when using this method.<ref name="NVIDIA" />

Line 140:

== Anti-aliasing ==

DLSS requires and applies its own [[anti-aliasing]] method. Thus, depending on the game and quality setting used, using DLSS may improve image quality even over native resolution rendering.<ref>{{Cite web |last=Smith |first=Matthew S. |date=2023-12-28 |title=What Is DLSS and Why Does it Matter for Gaming? |url=https://www.ign.com/articles/what-is-nvidia-dlss-meaning |access-date=2024-06-13 |website=IGN |language=en}}</ref> It operates on similar principles to [[Temporal anti-aliasing|TAA]]. Like TAA, it uses information from past frames to produce the current frame. Unlike TAA, DLSS does not sample every pixel in every frame. Instead, it samples different pixels in different frames and uses pixels sampled in past frames to fill in the unsampled pixels in the current frame. DLSS uses machine learning to combine samples in the current frame and past frames, and it can be thought of as an advanced and superior TAA implementation made possible by the available tensor cores.<ref name="NVIDIA" /> [[Nvidia]] also offers [[deepDeep learningLearning antiAnti-aliasingAliasing]] (DLAA), which provides the same AI-driven anti-aliasing DLSS uses, but without any upscaling or downscaling functionality.<ref name=":4" />

== Architecture ==