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The other thing I thought about was posing the problem as a contrastive representation learning problem. So I thought I could try something like CLIP (but with two vision networks instead of a vision and a language network) and learn to map similar pairs of images to be close to each other in representation space. I tried this, modifying the code here, but found that the loss was only coming down incredibly slowly.
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