VOID defeats mimicry in LDMs via stochasticity manipulation in the diffusion pipeline, raising average FID from 113 to 365 across evaluations.
Adversarial example does good: Pre- venting painting imitation from diffusion models via adversarial examples.arXiv preprint arXiv:2302.04578, 2023
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TS-LFO is a two-stage latent feature optimization method that bypasses state-of-the-art copyright defenses in diffusion-based image customization by restoring semantic consistency in latent space.
citing papers explorer
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VOID: Defeating Unauthorized Mimicry in Latent Diffusion Models
VOID defeats mimicry in LDMs via stochasticity manipulation in the diffusion pipeline, raising average FID from 113 to 365 across evaluations.
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Bypassing Copyright Protection in Diffusion-based Customization via Two-Stage Latent Feature Optimization
TS-LFO is a two-stage latent feature optimization method that bypasses state-of-the-art copyright defenses in diffusion-based image customization by restoring semantic consistency in latent space.