To address memorization in text-to-image diffusion styles, we suggest CAPTAIN, a education-cost-free framework that steers the denoising trajectory towards non-memorized outputs by injecting functions specifically into the latent denoising process with frequency decomposed noise initialization.
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Figure 3: Identifying the exceptional injection area for semantic enhancing. (Still left) Normal CLIP rating evolution across diffusion timesteps for each of the sdv1-five hundred memorized dataset. The injection region is bounded through the higher limit, exactly where the CLIP rating exceeds the typical (indicating strong semantic content), as well as reduced limit ahead of the sharp fall in the rate of modify.
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To determine the optimal injection window, we examine how picture–textual content alignment variations about the denoising trajectory. At Just about every timestep tt, the partly denoised latent tmathbf x _ t is decoded to image space and as opposed with the conditioning prompt mathbf p utilizing CLIP similarity:
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