Search Results for author: Jesús Malo

Found 14 papers, 3 papers with code

Disentangling the Link Between Image Statistics and Human Perception

no code implementations17 Mar 2023 Alexander Hepburn, Valero Laparra, Raúl Santos-Rodriguez, Jesús Malo

Moreover, the direct evaluation of the hypothesis was limited by the inability of the classical image models to deliver accurate estimates of the probability.


Psychophysics of Artificial Neural Networks Questions Classical Hue Cancellation Experiments

no code implementations15 Mar 2023 Jorge Vila-Tomás, Pablo Hernández-Cámara, Jesús Malo

In fact, the specific cancellation lights (and not the network architecture) are key to obtain human-like curves: results show that the classical choice of the lights is the one that leads to the best (more human-like) result, and any other choices lead to progressively different spectral sensitivities.

Analysis of Deep Image Quality Models

no code implementations26 Feb 2023 Pablo Hernández-Cámara, Jorge Vila-Tomás, Valero Laparra, Jesús Malo

In this work, we perform a thorough analysis of the perceptual properties of pre-trained nets (particularly their ability to predict image quality) by isolating different factors: the goal (the function), the data (learning environment), the architecture, and the readout: selected layer(s), fine-tuning of channel relevance, and use of statistical descriptors as opposed to plain readout of responses.


Orthonormal Convolutions for the Rotation Based Iterative Gaussianization

no code implementations8 Jun 2022 Valero Laparra, Alexander Hepburn, J. Emmanuel Johnson, Jesús Malo

Here we present the \emph{Convolutional RBIG}: an extension that alleviates this issue by imposing that the rotation in RBIG is a convolution.

Texture Synthesis

Neural Networks with Divisive normalization for image segmentation with application in cityscapes dataset

1 code implementation25 Mar 2022 Pablo Hernández-Cámara, Valero Laparra, Jesús Malo

In addition to the results on the Cityscapes and Foggy Cityscapes datasets, we explain these advantages through visualization of the responses: the equalization induced by the divisive normalization leads to more invariant features to local changes in contrast and illumination.

Image Segmentation Segmentation +1

On the relation between statistical learning and perceptual distances

no code implementations ICLR 2022 Alexander Hepburn, Valero Laparra, Raul Santos-Rodriguez, Johannes Ballé, Jesús Malo

Since machine learning relies on the statistics of training data as well, the above connection has interesting implications when using perceptual distances (which mimic the behavior of the human visual system) as a loss function.

BIG-bench Machine Learning Perceptual Distance +1

Information Theory in Density Destructors

2 code implementations2 Dec 2020 J. Emmanuel Johnson, Valero Laparra, Gustau Camps-Valls, Raul Santos-Rodríguez, Jesús Malo

Density destructors are differentiable and invertible transforms that map multivariate PDFs of arbitrary structure (low entropy) into non-structured PDFs (maximum entropy).

Synthesizing Visual Illusions Using Generative Adversarial Networks

no code implementations21 Nov 2019 Alexander Gomez-Villa, Adrian Martín, Javier Vazquez-Corral, Jesús Malo, Marcelo Bertalmío

Visual illusions are a very useful tool for vision scientists, because they allow them to better probe the limits, thresholds and errors of the visual system.

Generative Adversarial Network

PerceptNet: A Human Visual System Inspired Neural Network for Estimating Perceptual Distance

no code implementations28 Oct 2019 Alexander Hepburn, Valero Laparra, Jesús Malo, Ryan McConville, Raul Santos-Rodriguez

Traditionally, the vision community has devised algorithms to estimate the distance between an original image and images that have been subject to perturbations.

Perceptual Distance

Nonlinearities and Adaptation of Color Vision from Sequential Principal Curves Analysis

no code implementations31 Jan 2016 Valero Laparra, Sandra Jiménez, Gustavo Camps-Valls, Jesús Malo

Here we address the simultaneous statistical explanation of (i) the nonlinear behavior of achromatic and chromatic mechanisms in a fixed adaptation state, and (ii) the change of such behavior.

Iterative Gaussianization: from ICA to Random Rotations

7 code implementations IEEE Transactions on Neural Networks 2011 Valero Laparra, Gustavo Camps-Valls, Jesús Malo

The practical performance of RBIG is successfully illustrated in a number of multidimensional problems such as image synthesis, classification, denoising, and multi-information estimation.

Denoising Image Generation

Image Denoising with Kernels based on Natural Image Relations

no code implementations31 Jan 2016 Valero Laparra, Juan Gutiérrez, Gustavo Camps-Valls, Jesús Malo

In this paper, we propose an alternative non-explicit way to take into account the relations among natural image wavelet coefficients for denoising: we use support vector regression (SVR) in the wavelet domain to enforce these relations in the estimated signal.

Image Denoising

On the Suitable Domain for SVM Training in Image Coding

no code implementations18 Oct 2013 Gustavo Camps-Valls, Juan Gutiérrez, Gabriel Gómez-Pérez, Jesús Malo

We analytically demonstrate that no linear domain fulfills this condition because of the statistical and perceptual inter-coefficient relations that exist in these domains.

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