Deep Learning Super Sampling: Difference between revisions

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== 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 [[deep learning anti-aliasing]] (DLAA)., DLAAwhich provides the same AI-driven anti-aliasing DLSS uses, but without any upscaling or downscaling functionality.<ref name=":4" />
 
== Architecture ==