Search Results for author: José Lezama

Found 5 papers, 3 papers with code

Non-uniform Blur Kernel Estimation via Adaptive Basis Decomposition

1 code implementation1 Feb 2021 Guillermo Carbajal, Patricia Vitoria, Mauricio Delbracio, Pablo Musé, José Lezama

In recent years, the removal of motion blur in photographs has seen impressive progress in the hands of deep learning-based methods, trained to map directly from blurry to sharp images.

Deblurring Image Restoration

Overcoming the Disentanglement vs Reconstruction Trade-off via Jacobian Supervision

1 code implementation ICLR 2019 José Lezama

A major challenge in learning image representations is the disentangling of the factors of variation underlying the image formation.

Image Generation Image Reconstruction

Detecting Out-Of-Distribution Samples Using Low-Order Deep Features Statistics

no code implementations ICLR 2019 Igor M. Quintanilha, Roberto de M. E. Filho, José Lezama, Mauricio Delbracio, Leonardo O. Nunes

The ability to detect when an input sample was not drawn from the training distribution is an important desirable property of deep neural networks.

Psychophysics, Gestalts and Games

no code implementations25 May 2018 José Lezama, Samy Blusseau, Jean-Michel Morel, Gregory Randall, Rafael Grompone von Gioi

Using a computational quantitative version of the non-accidentalness principle, we raise the possibility that the psychophysical and the (older) gestaltist setups, both applicable on dot or Gabor patterns, find a useful complement in a Turing test.

Human Detection

OLÉ: Orthogonal Low-rank Embedding, A Plug and Play Geometric Loss for Deep Learning

1 code implementation5 Dec 2017 José Lezama, Qiang Qiu, Pablo Musé, Guillermo Sapiro

Deep neural networks trained using a softmax layer at the top and the cross-entropy loss are ubiquitous tools for image classification.

General Classification Metric Learning +2

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