Equilibrated Diffusion decomposes concepts in frequency space to independently optimize subject and style embeddings, plus mask-guided diffusion and residual reference attention, for improved subject fidelity and text alignment over baselines.
Unified multi-modal latent diffusion for joint subject and text conditional image generation
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HyperExpress extracts composable intrinsic concepts from single images via hyperbolic concept learning and concept-wise optimization in diffusion-based models.
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Equilibrated Diffusion: Frequency-aware Textual Embedding for Equilibrated Image Customization
Equilibrated Diffusion decomposes concepts in frequency space to independently optimize subject and style embeddings, plus mask-guided diffusion and residual reference attention, for improved subject fidelity and text alignment over baselines.
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Intrinsic Concept Extraction Based on Compositional Interpretability
HyperExpress extracts composable intrinsic concepts from single images via hyperbolic concept learning and concept-wise optimization in diffusion-based models.
- Adversarial Concept Distillation for One-Step Diffusion Personalization