DPOFusion uses direct preference optimization on property-aligned and preference-controllable latent diffusion models to produce adaptive infrared-visible image fusions aligned with heterogeneous human and machine vision demands.
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2 Pith papers cite this work. Polarity classification is still indexing.
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WaveGuard injects user-controlled, imperceptible frequency-based perturbations into synthetic images to reduce their value as training data for unauthorized knowledge distillation while preserving perceptual quality.
citing papers explorer
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Fusion in Your Way: Aligning Image Fusion with Heterogeneous Demands via Direct Preference Optimization
DPOFusion uses direct preference optimization on property-aligned and preference-controllable latent diffusion models to produce adaptive infrared-visible image fusions aligned with heterogeneous human and machine vision demands.
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Safeguarding Text-to-Image Generative Models Against Unauthorized Knowledge Distillation
WaveGuard injects user-controlled, imperceptible frequency-based perturbations into synthetic images to reduce their value as training data for unauthorized knowledge distillation while preserving perceptual quality.