Person
Alban Bornet
This person is no longer with EPFL
Related publications (11)
Global information processing in feedforward deep networks
Michael Herzog, Ben Henrik Lönnqvist, Adrien Christophe Doerig, Alban Bornet
While deep neural networks are state-of-the-art models of many parts of the human visual system, here we show that they fail to process global information in a humanlike manner. First, using visual crowding as a probe into global visual information process ...
2022Crowding and the importance of grouping and segmentation processes in human vision
Human vision has evolved to make sense of a world in which elements almost never appear in isolation. Surprisingly, the recognition of an element in a visual scene is strongly limited by the presence of other nearby elements, a phenomenon known as visual c ...
EPFL2021How crowding challenges (feedforward) convolutional neural networks
Michael Herzog, Ben Henrik Lönnqvist, Gregory Francis, Adrien Christophe Doerig, Alban Bornet, Lynn Schmittwilken
Are (feedforward) convolutional neural networks (CNNs) good models for the human visual system? Here, we used visual crowding as a well-controlled psychophysical test to probe CNNs. Visual crowding is a ubiquitous breakdown of object recognition in the hum ...
2021Global and high-level effects in crowding cannot be predicted by either high-dimensional pooling or target cueing
Michael Herzog, Adrien Christophe Doerig, Mauro Manassi, Alban Bornet, Oh-Hyeon Choung
In visual crowding, the perception of a target deteriorates in the presence of nearby flankers. Traditionally, target-flanker interactions have been considered as local, mostly deleterious, low-level, and feature specific, occurring when information is poo ...
ASSOC RESEARCH VISION OPHTHALMOLOGY INC2021Shrinking Bouma's window: How to model crowding in dense displays
Michael Herzog, Gregory Francis, Adrien Christophe Doerig, Alban Bornet
In crowding, perception of a target deteriorates in the presence of nearby flankers. Traditionally, it is thought that visual crowding obeys Bouma's law, i.e., all elements within a certain distance interfere with the target, and that adding more elements ...
PUBLIC LIBRARY SCIENCE2021Running Large-Scale Simulations on the Neurorobotics Platform to Understand Vision - The Case of Visual Crowding
Michael Herzog, Gregory Francis, Alban Bornet, Egidio Falotico, Alessandro Ambrosano
Traditionally, human vision research has focused on specific paradigms and proposed models to explain very specific properties of visual perception. However, the complexity and scope of modern psychophysical paradigms undermine the success of this approach ...
2019Beyond Bouma's window: How to explain global aspects of crowding?
Michael Herzog, Gregory Francis, Adrien Christophe Doerig, Aaron Michael Clarke, Alban Bornet
In crowding, perception of an object deteriorates in the presence of nearby elements. Although crowding is a ubiquitous phenomenon, since elements are rarely seen in isolation, to date there exists no consensus on how to model it. Previous experiments show ...
2019Capsule networks, but not convolutional networks explain global configurational visual effects
Michael Herzog, Adrien Christophe Doerig, Alban Bornet
In human vision, perception of local features depends on all elements in the visual field and their exact configuration. For example, observers performed a vernier discrimination task. When a surrounding square was added to the vernier, the task became muc ...
2019Shrinking Bouma's window: Visual crowding in dense displays
Michael Herzog, Gregory Francis, Adrien Christophe Doerig, Alban Bornet
In crowding, perception of a target deteriorates in the presence of nearby flankers. In the traditional feedforward framework of vision, only elements within Bouma’s window interfere with the target and adding more elements always leads to stronger crowdin ...
SAGE PUBLICATIONS LTD2019Using the Neurorobotics platform to explain global processing in visual crowding
Michael Herzog, Gregory Francis, Alban Bornet
The Neurorobotics Platform of the Human Brain Project hosts many different large-scale models that can easily be connected with each other. Here, we linked a deep neural network for saliency computation to a spiking cortical model for visual segmentation ( ...
2018