May 14, 2024, 4:47 a.m. | Nick Stracke, Stefan Andreas Baumann, Joshua M. Susskind, Miguel Angel Bautista, Bj\"orn Ommer

cs.CV updates on

arXiv:2405.07913v1 Announce Type: new
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 …

abstract arxiv become control forms generative generative models however image images information paper process resolution style text text-to-image tool type

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