17 papers
Do Vision Encoders Exhibit Human-like Color Thresholds?
Engy Ehab, Pablo Hernández-Cámara, Nahla Belal +3
Understanding and characterizing human color perception is a longstanding research goal. One of the most traditional approaches is looking for the human color discrimination thresh…
Leveraging Color Naming for Image Enhancement
David Serrano-Lozano, Luis Herranz, Michael S. Brown +1
Enhancing images to make them visually appealing is a persistent challenge in computer vision. Many deep-learning methods train models on paired datasets to replicate expert editin…
GLUT: 3D Gaussian Lookup Table for Continuous Color Transformation
Danna Xue, David Serrano-Lozano, Shaolin Su +1
3D Lookup Tables (3D LUTs) are widely used for color mapping, but their grid-based representation requires discretizing the RGB space, leading to a capacity-memory trade-off that b…
SyncLight: Single-Edit Multi-View Relighting
David Serrano-Lozano, Anand Bhattad, Luis Herranz +2
We present SyncLight, a method to enable consistent, parametric control over light sources across multiple uncalibrated views of a static scene conditioned on a single view. While…
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…
Evaluating Low-Light Image Enhancement Across Multiple Intensity Levels
Maria Pilligua, David Serrano-Lozano, Pai Peng +3
Imaging in low-light environments is challenging due to reduced scene radiance, which leads to elevated sensor noise and reduced color saturation. Most learning-based low-light enh…