collaborators

5 papers

cs.CV2026

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…

cs.CV2026

Mitigating Content Shift and Hallucination in GenAI Image Editing via Structural Refinement

Luxi Zhao, Michael S. Brown

Generative AI (GenAI) image editors, such as Nano Banana, produce visually compelling results for retouching tasks, enabling non-experts to edit images through text prompts alone.…

cs.CV2026

Addressing Image Authenticity When Cameras Use Generative AI

Umar Masud, Abhijith Punnappurath, Luxi Zhao +2

The ability of generative AI (GenAI) methods to photorealistically alter camera images has raised awareness about the authenticity of images shared online. Interestingly, images ca…

cs.CV2026

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…

cs.CV2025

Revisiting Image Fusion for Multi-Illuminant White-Balance Correction

David Serrano-Lozano, Aditya Arora, Luis Herranz +3

White balance (WB) correction in scenes with multiple illuminants remains a persistent challenge in computer vision. Recent methods explored fusion-based approaches, where a neural…