7 papers
LumiCtrl : Learning Illuminant Prompts for Lighting Control in Personalized Text-to-Image Models
Muhammad Atif Butt, Kai Wang, Javier Vazquez-Corral +1
Text-to-image (T2I) models have demonstrated remarkable progress in creative image generation, yet they still lack precise control over scene illuminants which is a crucial factor…
NumColor: Precise Numeric Color Control in Text-to-Image Generation
Muhammad Atif Butt, Diego Hernandez, Alexandra Gomez-Villa +3
Text-to-image diffusion models excel at generating images from natural language descriptions, yet fail to interpret numerical colors such as hex codes (#FF5733) and RGB values (rgb…
Leveraging Semantic Attribute Binding for Free-Lunch Color Control in Diffusion Models
Héctor Laria, Alexandra Gomez-Villa, Jiang Qin +5
Recent advances in text-to-image (T2I) diffusion models have enabled remarkable control over various attributes, yet precise color specification remains a fundamental challenge. Ex…
GenColorBench: A Color Evaluation Benchmark for Text-to-Image Generation Models
Muhammad Atif Butt, Alexandra Gomez-Villa, Tao Wu +3
Recent years have seen impressive advances in text-to-image generation, with image generative or unified models producing high-quality images from text. Yet these models still stru…
Color Names in Vision-Language Models
Alexandra Gomez-Villa, Pablo Hernández-Cámara, Muhammad Atif Butt +3
Color serves as a fundamental dimension of human visual perception and a primary means of communicating about objects and scenes. As vision-language models (VLMs) become increasing…
An h-space Based Adversarial Attack for Protection Against Few-shot Personalization
Xide Xu, Sandesh Kamath, Muhammad Atif Butt +1
The versatility of diffusion models in generating customized images from few samples raises significant privacy concerns, particularly regarding unauthorized modifications of priva…