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cs.CV2026

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2024

Privacy Protection in Personalized Diffusion Models via Targeted Cross-Attention Adversarial Attack

Xide Xu, Muhammad Atif Butt, Sandesh Kamath +1

The growing demand for customized visual content has led to the rise of personalized text-to-image (T2I) diffusion models. Despite their remarkable potential, they pose significant…