![]() Using just a single frame for upscaling means the neural network itself must generate a large amount of new information to produce the high resolution output, this can result in slight hallucinations such as leaves that differ in style to the source content. The second stage is an image upscaling step which uses the single raw, low-resolution frame to upscale the image to the desired output resolution. The first step is an image enhancement network which uses the current frame and motion vectors to perform edge enhancement, and spatial anti-aliasing. The first iteration of DLSS is a predominantly spatial image upscaler with two stages, both relying on convolutional auto-encoder neural networks. For example, a 1080p scene with a 50% render scale would have an internal resolution of 540p.
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