14 citations · 15 across the 7 of their papers we have counts for
10 papers
Beyond the Linear Representation Hypothesis: Non-Linear Activation Steering in Text-to-Image Models
Muhammad Atif Butt, Paweł Skierś, Joost Van De Weijer +1
Mechanistic interpretability often relies on the Linear Representation Hypothesis (LRH), which assumes that high-level concepts are encoded as linear directions in activation space…
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…
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…
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…
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…
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…
ColorPeel: Color Prompt Learning with Diffusion Models via Color and Shape Disentanglement
Muhammad Atif Butt, Kai Wang, Javier Vazquez-Corral +1
Text-to-Image (T2I) generation has made significant advancements with the advent of diffusion models. These models exhibit remarkable abilities to produce images based on textual p…
Dynamic Prompt Learning: Addressing Cross-Attention Leakage for Text-Based Image Editing
Kai Wang, Fei Yang, Shiqi Yang +2
Large-scale text-to-image generative models have been a ground-breaking development in generative AI, with diffusion models showing their astounding ability to synthesize convincin…