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RB-Modulation RB-Modulation: Training-Free Stylization using Reference-Based Modulation Litu Rout 1,2 Yujia Chen 2 Nataniel Ruiz 2 Abhishek Kumar 3 Constantine Caramanis 1 Sanjay Shakkottai 1 Wen-Sheng Chu 2 1 University of Texas, Austin   2 Google   3 Google DeepMind ICLR 2025 (Oral: 1.8% acceptance ratio) [Paper] [OpenReview] [ArXiv] [Code] [Demo] Given a single reference image (rounded rectangle), our method RB-Modulation offers a training-free plug-and-play solution for (a) stylization, and (b) content-style composition with various prompts while maintaining sample diversity and prompt alignment. For instance, given a reference style image (e.g. “melting golden 3d rendering style”) and content image (e.g. (A) “dog”), our method adheres to the desired prompts without leaking contents from the reference style image and without being restricted to the pose of the reference content image. Abstract We pr...
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