Publication

Capsule networks, but not convolutional networks explain global configurational visual effects

Publications associées (76)

Graph Chatbot

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

Connectez-vous pour utiliser Chat avec Graph Search

The Robustness of Deep Networks - A geometric perspective

Pascal Frossard, Seyed Mohsen Moosavi Dezfooli, Alhussein Fawzi

Deep neural networks have recently shown impressive classification performance on a diverse set of visual tasks. When deployed in real-world (noise-prone) environments, it is equally important that these classifiers satisfy robustness guarantees: small per ...

Institute of Electrical and Electronics Engineers2017

Theory of representation learning in cortical neural networks

Carlos Stein Naves de Brito

Our brain continuously self-organizes to construct and maintain an internal representation of the world based on the information arriving through sensory stimuli. Remarkably, cortical areas related to different sensory modalities appear to share the same f ...

EPFL2016

What crowding can tell us about object representations

Michael Herzog, Aaron Michael Clarke, Mauro Manassi

In crowding, perception of a target usually deteriorates when flanking elements are presented next to the target. Surprisingly, adding further flankers can lead to a release from crowding. In previous work we showed that, for example, vernier offset discri ...

Association for Research in Vision and Ophthalmology (ARVO)2016

Putting low-level vision into global context: Why vision cannot be reduced to basic circuits

Michael Herzog, Yvonne Evelina Thunell

To cope with the complexity of vision, most models in neuroscience and computer vision are of hierarchical and feedforward nature. Low-level vision, such as edge and motion detection, is explained by basic low-level neural circuits, whose outputs serve as ...

Elsevier2016

Visual Link Retrieval in a Database of Paintings

Frédéric Kaplan, Isabella Di Lenardo, Benoît Laurent Auguste Seguin, Carlotta Striolo

This paper examines how far state-of-the-art machine vision algorithms can be used to retrieve common visual patterns shared by series of paintings. The research of such visual patterns, central to Art History Research, is challenging because of the divers ...

2016

Targets but not flankers are suppressed in crowding as revealed by EEG frequency tagging

Michael Herzog, Vitaly Chicherov

Perception of a visual target can strongly deteriorate in the presence of flanking elements (crowding). For example, adding lines next to a vernier makes vernier offset discrimination difficult. Crowding is often considered a bottleneck of low-level vision ...

Elsevier2015

Contour erasure and filling-in: Old simulations account for most new observations

Gregory Francis

Three recent studies used similar stimulus sequences to investigate mechanisms for brightness perception. Anstis and Greenlee (2014) demonstrated that adaptation to a flickering black and white outline erased the visibility of a subsequent target shape def ...

Pion Ltd2015

Vision in clutter

Vitaly Chicherov

Perception of a visual target can strongly deteriorate in the presence of flanking elements (crowding). Crowding is the main limiting factor in reading and a major contributor to poor vision in amblyopia. In crowding, elements appear jumbled and thus are h ...

EPFL2015

Crowding and shape representations

Michael Herzog, Aaron Michael Clarke, Mauro Manassi

In crowding, target perception deteriorates when flanking elements are added. Crowding is traditionally characterized by target-flanker interactions which are (1) deleterious, (2) spatially confined within Bouma’s window, and (3) feature specific. Here, we ...

Sage Publications Ltd2015

Biologically Inspired Keypoints

Alexandre Massoud Alahi

This chapter describes methods to extract and represent biologically inspired keypoints. It highlights the design choices that are not contradictory to the current understanding of the human visual system (HVS). The chapter briefly defines some terminologi ...

Wiley2015