Carlos Rodríguez - Pardo

Seddi

Textures made of regular repeating patterns are ubiquitous in the real world, most notably in man-made environments. They are defined by the presence of a repeating element, which can show a significant amount of random variations, non-rigid deformations or color noise. We propose an end-to-end pipeline capable of finding the size of the minimal re...

The use of computational methods to evaluate aesthetics in photography has gained interest in recent years due to the popularization of convolutional neural networks and the availability of new annotated datasets. Most studies in this area have focused on designing models that do not take into account individual preferences for the prediction of th...

We present a deep learning-based method for propagating spatially-varying visual material attributes (e.g. texture maps or image stylizations) to larger samples of the same or similar materials. For training, we leverage images of the material taken under multiple illuminations and a dedicated data augmentation policy, making the transfer robust to...

Real-time graphics applications require high-quality textured materials to convey realism in virtual environments. Generating these textures is challenging as they need to be visually realistic, seamlessly tileable, and have a small impact on the memory consumption of the application. For this reason, they are often created manually by skilled arti...

Intrinsic imaging or intrinsic image decomposition has traditionally been described as the problem of decomposing an image into two layers: a reflectance, the albedo invariant color of the material; and a shading, produced by the interaction between light and geometry. Deep learning techniques have been broadly applied in recent years to increase t...

The unprecedented growth in the amount and variety of data we can store about the behaviour of customers has been parallel to the popularization and development of machine learning algorithms. This confluence of factors has created the opportunity of understanding customer behaviour and preferences in ways that were undreamt of in the past. In this...

Intrinsic imaging or intrinsic image decomposition has traditionally been described as the problem of decomposing an image into two layers: a reflectance, the albedo invariant color of the material; and a shading, produced by the interaction between light and geometry. Deep learning techniques have been broadly applied in recent years to increase t...

The unprecedented growth in the amount and variety of data we can store about the behaviour of customers has been parallel to the popularization and development of machine learning algorithms. This confluence of factors has created the opportunity of understanding customer behaviour and preferences in ways that were undreamt of in the past. In this...

Textures made of regular repeating patterns are ubiquitous in the real world, most notably in man-made environments. They are defined by the presence of a repeating element, which can show a significant amount of random variations, non-rigid deformations or color noise. We propose an end-to-end pipeline capable of finding the size of the minimal re...

The use of computational methods to evaluate aesthetics in photography has gained interest in recent years due to the popularization of convolutional neural networks and the availability of new annotated datasets. Most studies in this area have focused on designing models that do not take into account individual preferences for the prediction of th...

The new technologies for data analysis, such as decision tree learning, may help to predict the risk of developing diseases. The aim of the present work was to develop a pilot decision tree learning to predict overweight/obesity based on the combination of six single nucleotide polymorphisms (SNP) located in feeding-associated genes. Genotype study...

We propose a transfer-learning method capable of surpassing the state-of-the-art results in predicting personalised preferences in aesthetics in photography, while eliminating the need for data about the contents and styles of the pictures. Our methodology allows the creation of end-to-end user-specific aesthetic prediction models with a smaller se...

Data analysis is comprised of a set of processes that allows a key support for making better decisions. The ability to analyse data in the field of retail trade allows companies to obtain valuable information such as understanding the profile of customers who demand a particular type of product, optimizing the price of certain products, identifying...

This work has been developed within the project of Applied Artificial Intelligence Group at UC3M, called ”Augmented Science”, in order to disseminate and support education in science through Augmented Reality (AR) tools. The project is part of new developments provided with AR systems on mobile devices and their application in promoting science tea...