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> solves the same problem set with the same or better performance

The games industry has spent the last decade adopting techniques that misleadingly inflate the simple, easily-quantified metrics of FPS and resolution, by sacrificing quality in ways that are harder to quantify. Until you have good metrics for quantifying the motion artifacts and blurring introduced by post-processing AA, upscaling, and temporal AA or frame generation, it's dishonest to claim that those techniques solve the same problem with better performance. They're giving you a worse image, and pointing to the FPS numbers as evidence that they're adequate is focusing on entirely the wrong side of the problem.

That's not to say those techniques aren't sometimes the best available tradeoff, but it's wrong to straight-up ignore the downsides because they're hard to measure.



This has long been the aspect I've struggled with, having spent some time implementing various temporal solutions in the past 2 years. We can try and pull out all sorts of classic metrics like SSIM, but the truth is a lot of these effects are really hard to objectively evaluate using some sort of metric. Moreover the same technique can have vastly different outcomes depending on the content, and user perception is subjective as well. Many days were spent thinking I had solved a visual issue, only for another edge case to come up under specific conditions. Many of these techniques are fairly difficult to reason about from first-principles and adding ML into the mix only makes that harder.




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