This post is going to introduce you a technology related to image DLSS (deep learning super sampling).

It focuses on the basic definition, revolution, working principle, as well as program.

The image generated by this technology looks like a higher-resolution image without the rendering overhead.

To obtain more details about DLSS, keep reading this post ofMiniTool.

Then the data pipe learns how to improve the image to anti-aliasing quality without requiring any performance overhead.

The trained neural internet will be packaged into a video game driver and then run during the game play.

At present, DLSS is enabled on NVIDIA RTX20 Series GPU card with a number of video games.

However, DLSS only supported a few video games like Battlefield V and Metro Exodus at that time.

NVIDIA released a new version calledDLSS 2.0in April 2020.

This version supported a few existing games including Control and Wolfenstein: Youngblood.

It used the Tensor Cores and the AI didnt need to be trained specifically on each game.

But DLSS 2.0 cannot work well with anti-aliasing techniques like MSAA and TSAA.

Whats more, the performance of DLSS will be affected when the techniques are enabled on top of DLSS.

Since April 2020, DLSS 2.0 has become a must element on a per-game basis.

DLSS does this by making using of some anti-aliasing effects and some automated sharpening.

Artificial intelligence algorithm is trained to look at certain games at extremely high resolutions (64x super-sampling).

Previously, NVIDIA must go through this process game by game.

With the existence of DLSS 2.0, A.I.

model doesnt need to be trained for each game.

The Function of DLSS

DLSS is the final result of NVIDIAs A.I.

algorithm detailed teaching process that is aimed at generating better-looking games.

With DLSS 2.0, you might render games at 1080p while outputting them at 4k.

Some conventional super-resolution techniques can cause artifacts and bugs in the eventual picture.

NVIDIA DLSS is built to handle those errors to generate a better-looking image.

You may have learned the answer from the post now.

Here comes the end of the post!