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Found 6 papers, 1 papers with code
Using Decoupled Features for Photo-realistic Style Transfer
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.
Matching visual induction effects on screens of different size
In the film industry, the same movie is expected to be watched on displays of vastly different sizes, from cinema screens to mobile phones.
Synthesizing Visual Illusions Using Generative Adversarial Networks
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.
Cortical-inspired Wilson-Cowan-type equations for orientation-dependent contrast perception modelling
We consider the evolution model proposed in [9, 6] to describe illusory contrast perception phenomena induced by surrounding orientations.
A cortical-inspired model for orientation-dependent contrast perception: a link with Wilson-Cowan equations
We consider a differential model describing neuro-physiological contrast perception phenomena induced by surrounding orientations.
Convolutional Neural Networks Deceived by Visual Illusions
In particular, we show that CNNs trained for image denoising, image deblurring, and computational color constancy are able to replicate the human response to visual illusions, and that the extent of this replication varies with respect to variation in architecture and spatial pattern size.
