Even the Tottenham Hotspurs logo in the top-right looks much better on the 720p upscaled sample than on the 480p upscaling (sorry about that overlay on the one image). And the 480p to 4K upscale (20.25x upscale!) is still missing a ton of detail, like you can't see the strands of the net in either the VSR or non-VSR content. Starting with a 720p source and upscaling to 4K (9x upscale) will be more difficult than going from 1080p to 4K (4x upscaling). It's not a massive improvement in any of the sports samples, but there's definitely some sharpening and deblocking that, at least in our subjective view, looks better.
You can still clearly see the differences between the normal upscaling (in Chrome) versus the VSR upscaling. But whatever the exact details, let's talk about how it looks.Īll those images are 4K JPG, with maximum quality - not lossless, but we can't exceed 10MB, so some slight compression was required. So while in theory VSR could use the current and previous frame data, it appears Nvidia has opted for a pure spatial upscaling approach. With VSR, there's no pre-computed depth buffer or motion vectors to speak of, so everything needs to be done based purely on the video frames. Combined with the previous frame(s) and the trained AI network to generate upscaled and anti-aliased frames. There are plenty of differences between VSR and DLSS, of course.įor one, DLSS gets data directly from the game engine, including the current frame, motion vectors, and depth buffers.
Take a bunch of paired images, with each pair containing a low-resolution and lower bitrate version of a higher resolution (and higher quality) video frame, and run that through a deep learning training algorithm to teach the network how to ideally upscale and enhance lower quality input frames into better-looking outputs. The basic summary of the algorithm should sound familiar to anyone with knowledge of DLSS.
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