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Learning V1 Simple Cells with Vector Representation of Local Content and Matrix Representation of Local Motion

Related publications (43)

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Probing and modulating inter-areal coupling in the cortical visual motion processing pathway with non-invasive brain stimulation

Michele Bevilacqua

In the last few years, stroke ranked as the second most common cause of death and is the third most significant condition affecting disability-adjusted life years (DALYs) worldwide. Being the most prevalent and quality of life impacting post-stroke symptom ...

EPFL2024

Unsupervised Visual Entity Abstraction towards 2D and 3D Compositional Models

Beril Besbinar

Object-centric learning has gained significant attention over the last years as it can serve as a powerful tool to analyze complex scenes as a composition of simpler entities. Well-established tasks in computer vision, such as object detection or instance ...

EPFL2022

Crowding and the importance of grouping and segmentation processes in human vision

Alban Bornet

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 ...

EPFL2021

Visual Focus of Attention Estimation in 3D Scene with an Arbitrary Number of Targets

Jean-Marc Odobez, Rémy Alain Siegfried

Visual Focus of Attention (VFOA) estimation in conversation is challenging as it relies on difficult to estimate information (gaze) combined with scene features like target positions and other contextual information (speaking status) allowing to disambigua ...

IEEE COMPUTER SOC2021

Contextually Plausible and Diverse 3D Human Motion Prediction

Mathieu Salzmann, Fatemehsadat Saleh

We tackle the task of diverse 3D human motion prediction, that is, forecasting multiple plausible future 3D poses given a sequence of observed 3D poses. In this context, a popular approach consists of using a Conditional Variational Autoencoder (CVAE). How ...

IEEE2021

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Convolutional neural networks (CNN) are known to learn an image representation that captures concepts relevant to the task, but do so in an implicit way that hampers model interpretability. However, one could argue that such a representation is hidden in t ...

LNCS2020

Generalized Mullineux Involution And Perverse Equivalences

Thomas Gerber

We define a generalization of the Mullineux involution on multipartitions using the theory of crystals for higher-level Fock spaces. Our generalized Mullineux involution turns up in representation theory via two important derived functors on cyclotomic Che ...

2020

Running 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 ...

2019

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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 ...

2019

New Approaches to Artistic Synthesis Relying on Visual Perception

Mahmut Sami Arpa

Artists often take advantage of the limitations of the human visual system to create art that provides new experiences for the observers. Similarly, in this thesis, we explore new computational artistic compositions that create new visual experiences by re ...

EPFL2019