most citedMoA: Mixture-of-Attention for Subject-Context Disentanglement in Personalized Image Generation

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cs.CV2025

Nested Attention: Semantic-aware Attention Values for Concept Personalization

Or Patashnik, Rinon Gal, Daniil Ostashev +3

Personalizing text-to-image models to generate images of specific subjects across diverse scenes and styles is a rapidly advancing field. Current approaches often face challenges i…

cs.CV2024★ 1 cited

MoA: Mixture-of-Attention for Subject-Context Disentanglement in Personalized Image Generation

Kuan-Chieh Wang, Daniil Ostashev, Yuwei Fang +2

We introduce a new architecture for personalization of text-to-image diffusion models, coined Mixture-of-Attention (MoA). Inspired by the Mixture-of-Experts mechanism utilized in l…