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That is not how image-to-image approaches work.

ControlNet is a obvious counterexample. If you think "diffusion is just collaging", upload a control image using this space that cannot exist in the source dataset (e.g. a personal sketch) and generate your own image: https://huggingface.co/spaces/AP123/IllusionDiffusion



It’s not that I think it’s purely collage, but that inputting a high-quality image doesn’t somehow lead to generating better quality output by default. The various silly images created by using keywords like “Greek sculpture” or “Mona Lisa” are an example.




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