Recently, deep learning based inpainting methods have shown promising performance, in
which some multi-scale networks are introduced to characterize image content in both …

Deep learning based inpainting methods have obtained promising performance for image
restoration, however current image inpainting methods still tend to produce unreasonable …

We reproduce suprathreshold perception phenomena, specifically visual illusions, by Wilson–
Cowan (WC)-type models of neuronal dynamics. Our findings show that the ability to …

An extended four-dimensional version of the traditional Petitot–Citti–Sarti model on contour
completion in the visual cortex is examined. The neural configuration space is considered as …

We consider the evolution model proposed in Bertalmío (Front Comput Neurosci 8: 71,
2014), Bertalmío et al.(IEEE Trans Image Process 16 (4): 1058–1072, 2007) to describe …

This book proposes a semi-discrete version of the theory of Petitot and Citti-Sarti, leading to
a left-invariant structure over the group SE (2, N), restricted to a finite number of rotations …

Two key ideas have greatly improved techniques for image enhancement and denoising:
the lifting of image data to multi-orientation distributions and the application of nonlinear …

We present a novel cortically-inspired image completion algorithm. It uses five-dimensional
sub-Riemannian cortical geometry, modeling the orientation, spatial frequency and phase …

Recently, deep learning has made great achievements in the field of image inpainting,
especially filling the large missing regions based on generative adversarial net (GAN) …

This paper introduces the sigma flow model for the prediction of structured labelings of data
observed on Riemannian manifolds, including Euclidean image domains as special case …