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Only-Style: Stylistic Consistency in Image Generation without Content Leakage

Title: Only-Style: Stylistic Consistency in Image Generation without Content Leakage
Authors: Aravanis, Tilemachos; Filntisis, Panagiotis; Maragos, Petros; Retsinas, George
Publication Year: 2025
Collection: ArXiv.org (Cornell University Library)
Subject Terms: Computer Vision and Pattern Recognition
Description: Generating images in a consistent reference visual style remains a challenging computer vision task. State-of-the-art methods aiming for style-consistent generation struggle to effectively separate semantic content from stylistic elements, leading to content leakage from the image provided as a reference to the targets. To address this challenge, we propose Only-Style: a method designed to mitigate content leakage in a semantically coherent manner while preserving stylistic consistency. Only-Style works by localizing content leakage during inference, allowing the adaptive tuning of a parameter that controls the style alignment process, specifically within the image patches containing the subject in the reference image. This adaptive process best balances stylistic consistency with leakage elimination. Moreover, the localization of content leakage can function as a standalone component, given a reference-target image pair, allowing the adaptive tuning of any method-specific parameter that provides control over the impact of the stylistic reference. In addition, we propose a novel evaluation framework to quantify the success of style-consistent generations in avoiding undesired content leakage. Our approach demonstrates a significant improvement over state-of-the-art methods through extensive evaluation across diverse instances, consistently achieving robust stylistic consistency without undesired content leakage.
Document Type: text
Language: unknown
Relation: http://arxiv.org/abs/2506.09916
Availability: http://arxiv.org/abs/2506.09916
Accession Number: edsbas.7CA29DFE
Database: BASE