2 citations · 2 across the 2 of their papers we have counts for
6 papers
Disentanglement of Color and Shape Representations for Continual Learning
David Berga, Marc Masana, Joost Van de Weijer
We hypothesize that disentangled feature representations suffer less from catastrophic forgetting. As a case study we perform explicit disentanglement of color and shape, by adjust…
MineGAN: effective knowledge transfer from GANs to target domains with few images
Yaxing Wang, Abel Gonzalez-Garcia, David Berga +3
One of the attractive characteristics of deep neural networks is their ability to transfer knowledge obtained in one domain to other related domains. As a result, high-quality netw…
SID4VAM: A Benchmark Dataset with Synthetic Images for Visual Attention Modeling
David Berga, Xosé R. Fdez-Vidal, Xavier Otazu +1
A benchmark of saliency models performance with a synthetic image dataset is provided. Model performance is evaluated through saliency metrics as well as the influence of model ins…
Modeling Bottom-Up and Top-Down Attention with a Neurodynamic Model of V1
David Berga, Xavier Otazu
Previous studies suggested that lateral interactions of V1 cells are responsible, among other visual effects, of bottom-up visual attention (alternatively named visual salience or…
Psychophysical evaluation of individual low-level feature influences on visual attention
David Berga, Xosé Ramón Fdez-Vidal, Xavier Otazu +2
In this study we provide the analysis of eye movement behavior elicited by low-level feature distinctiveness with a dataset of synthetically-generated image patterns. Design of vis…
A Neurodynamic model of Saliency prediction in V1
David Berga, Xavier Otazu
Lateral connections in the primary visual cortex (V1) have long been hypothesized to be responsible of several visual processing mechanisms such as brightness induction, chromatic…