A-watermark-for-Diffusion-Models
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different crop result from paper
Different from the result reported in the paper of random crop, it turns out that the bit accuracy of crop with ratio 0.9 achieves about 0.6, and ratio 0.7 or less achieves about 0.5.
Did you also achieve this result?
I think this result might be reasonable because the whole latent is divided into chunks of 256 bits, and then voting is done on each position. However, the positions themselves may not correspond to the correct starting point.
Maybe for extraction we need to start from different points and choose the best result? I'm not sure if my analysis is correct.