Harmonizing Attention: Training-Free Texture-Aware Geometry Transfer

Eito Ikuta, Yohan Lee, Akihiro Iohara, Yu Saito, Toshiyuki Tanaka; Proceedings of the Winter Conference on Applications of Computer Vision (WACV), 2025, pp. 2042-2051

Creating images where surface patterns of one object - such as cracks holes or grooves - are precisely transferred onto objects made of different materials remains a challenging task in computer graphics. For example recreating the exact pattern of wood grain cracks on a metallic surface while maintaining the realistic metallic texture requires sophisticated technical solutions. In this study we introduce Harmonizing Attention a new method that can automatically extract these surface patterns from photographs and recreate them with different materials while preserving natural-looking textures. Our approach achieves this through a novel attention mechanism that can process multiple reference images simultaneously without requiring additional training. This makes the method both practical and efficient for real-world applications opening up new possibilities in augmented reality image editing and beyond.