Search Results for author: Javier Portilla

Found 3 papers, 1 papers with code

Evaluating Perceptual Distances by Fitting Binomial Distributions to Two-Alternative Forced Choice Data

no code implementations15 Mar 2024 Alexander Hepburn, Raul Santos-Rodriguez, Javier Portilla

The two-alternative forced choice (2AFC) experimental setup is popular in the visual perception literature, where practitioners aim to understand how human observers perceive distances within triplets that consist of a reference image and two distorted versions of that image.

Decision Making Perceptual Distance

Using Decoupled Features for Photo-realistic Style Transfer

1 code implementation5 Dec 2022 Trevor D. Canham, Adrián Martín, Marcelo Bertalmío, Javier Portilla

In this work we propose a photorealistic style transfer method for image and video that is based on vision science principles and on a recent mathematical formulation for the deterministic decoupling of sample statistics.

Style Transfer

Deterministic Decoupling of Global Features and its Application to Data Analysis

no code implementations5 Jul 2022 Eduardo Martinez-Enriquez, Maria del Mar Gonzalez, Javier Portilla

We introduce a method for deterministic decoupling of global features and show its applicability to improve data analysis performance, as well as to open new venues for feature transfer.

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