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arXiv · 2405.07913

CTRLorALTer: Conditional LoRAdapter for Efficient 0-Shot Control & Altering of T2I Models

Nick Stracke·Stefan Andreas Baumann·Joshua M. Susskind·Miguel Angel Bautista·Björn Ommer
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Abstract

Text-to-image generative models have become a prominent and powerful tool that excels at generating high-resolution realistic images. However, guiding the generative process of these models to consider detailed forms of conditioning reflecting style and/or structure information remains an open problem. In this paper, we present LoRAdapter, an approach that unifies both style and structure conditioning under the same formulation using a novel conditional LoRA block that enables zero-shot control. LoRAdapter is an efficient, powerful, and architecture-agnostic approach to condition text-to-image diffusion models, which enables fine-grained control conditioning during generation and outperforms recent state-of-the-art approaches.

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Nick Stracke, Stefan Andreas Baumann, Joshua M. Susskind, Miguel Angel Bautista, Björn Ommer. 2024-05-13. CTRLorALTer: Conditional LoRAdapter for Efficient 0-Shot Control & Altering of T2I Models. https://arxiv.org/abs/2405.07913

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