papers

Publications (10)

cs.CV2025

Color encoding in Latent Space of Stable Diffusion Models

Guillem Arias, Ariadna SolÃ, Martí Armengod +1

Recent advances in diffusion-based generative models have achieved remarkable visual fidelity, yet a detailed understanding of how specific perceptual attributes - such as color an…

cs.CV2024

Learning Relighting and Intrinsic Decomposition in Neural Radiance Fields

Yixiong Yang, Shilin Hu, Haoyu Wu +3

The task of extracting intrinsic components, such as reflectance and shading, from neural radiance fields is of growing interest. However, current methods largely focus on syntheti…

cs.CV2020

Deep intrinsic decomposition trained on surreal scenes yet with realistic light effects

Hassan Sial, Ramon Baldrich, Maria Vanrell

Estimation of intrinsic images still remains a challenging task due to weaknesses of ground-truth datasets, which either are too small or present non-realistic issues. On the other…

cs.CV2024

Relighting from a Single Image: Datasets and Deep Intrinsic-based Architecture

Yixiong Yang, Hassan Ahmed Sial, Ramon Baldrich +1

Single image scene relighting aims to generate a realistic new version of an input image so that it appears to be illuminated by a new target light condition. Although existing wor…

cs.CV2020

Light Direction and Color Estimation from Single Image with Deep Regression

Hassan A. Sial, Ramon Baldrich, Maria Vanrell +1

We present a method to estimate the direction and color of the scene light source from a single image. Our method is based on two main ideas: (a) we use a new synthetic dataset wit…

cs.CV2019

Understanding trained CNNs by indexing neuron selectivity

Ivet Rafegas, Maria Vanrell, Luis A. Alexandre +1

The impressive performance of Convolutional Neural Networks (CNNs) when solving different vision problems is shadowed by their black-box nature and our consequent lack of understan…

cs.CV2020

Intrinsic Decomposition of Document Images In-the-Wild

Sagnik Das, Hassan Ahmed Sial, Ke Ma +3

Automatic document content processing is affected by artifacts caused by the shape of the paper, non-uniform and diverse color of lighting conditions. Fully-supervised methods on r…

cs.CV2025

Color in Visual-Language Models: CLIP deficiencies

Guillem Arias, Ramon Baldrich, Maria Vanrell

This work explores how color is encoded in CLIP (Contrastive Language-Image Pre-training) which is currently the most influential VML (Visual Language model) in Artificial Intellig…

cs.CV2024

MLI-NeRF: Multi-Light Intrinsic-Aware Neural Radiance Fields

Yixiong Yang, Shilin Hu, Haoyu Wu +3

Current methods for extracting intrinsic image components, such as reflectance and shading, primarily rely on statistical priors. These methods focus mainly on simple synthetic sce…

cs.CV2015

Understanding learned CNN features through Filter Decoding with Substitution

Ivet Rafegas, Maria Vanrell

In parallel with the success of CNNs to solve vision problems, there is a growing interest in developing methodologies to understand and visualize the internal representations of t…