5 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…
Covariances for Free: Exploiting Mean Distributions for Training-free Federated Learning
Dipam Goswami, Simone Magistri, Kai Wang +3
Using pre-trained models has been found to reduce the effect of data heterogeneity and speed up federated learning algorithms. Recent works have explored training-free methods usin…
The Art of Deception: Color Visual Illusions and Diffusion Models
Alex Gomez-Villa, Kai Wang, Alejandro C. Parraga +4
Visual illusions in humans arise when interpreting out-of-distribution stimuli: if the observer is adapted to certain statistics, perception of outliers deviates from reality. Rece…