AttnMod: Attention-Based New Art Styles
Shih-Chieh Su

TL;DR
AttnMod is a training-free technique that modifies cross-attention in pre-trained diffusion models to create diverse, unpromptable art styles, enhancing the expressive capacity of text-to-image generation.
Contribution
It introduces a novel attention modulation method that enables stylistic transformations without retraining or changing prompts.
Findings
Enables diverse stylistic transformations
Does not require retraining or prompt changes
Expands expressive capacity of diffusion models
Abstract
We introduce AttnMod, a training-free technique that modulates cross-attention in pre-trained diffusion models to generate novel, unpromptable art styles. The method is inspired by how a human artist might reinterpret a generated image, for example by emphasizing certain features, dispersing color, twisting silhouettes, or materializing unseen elements. AttnMod simulates this intent by altering how the text prompt conditions the image through attention during denoising. These targeted modulations enable diverse stylistic transformations without changing the prompt or retraining the model, and they expand the expressive capacity of text-to-image generation.
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Taxonomy
TopicsAesthetic Perception and Analysis · Digital Media and Visual Art · Art Education and Development
MethodsSoftmax · Attention Is All You Need · Diffusion
