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[D] Content & Style disentanglement for video-game texture superresolution

Some games (like early 3D platformers) tend to have drastically different style from another, often mainstream games, in terms of its cartoony or perhaps photorealistic look. The superresolution networks that NVIDIA used doesn’t use disentanglement i believe, which possibly restricts its generalization and usage on ultra-LQ textures..

Might someone look into joining games with similiar graphics styles from early era and todays’s era (even though the style similiarity is questionable, sometimes games within the same franchises look different, so perhaps a style disentangler trained on regular datasets might be used to diffrentiate between ’em) and learn a network to recognize a style and generate high-resolution details based on dat ?

submitted by /u/ad48hp
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.