Dynamic Visual Attention on the Sphere

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Vision-based Flocking in Aerial Robot Swarms

Fabian Maximilian Schilling

Aerial robot swarms have the potential to perform time-critical and dangerous tasks such as disaster response without compromising human safety. However, their reliance on external infrastructure such as global positioning for localization and wireless net ...

EPFL2022

A Lightweight Goal-Based model for Trajectory Prediction

Kaouther Messaoud Ben Amor

We present a lightweight goal-based model for multimodal, probabilistic trajectory prediction for urban driving. Previous conditioned-on-goal methods have used map information in order to establish a set of potential goals and then complete the correspondi ...

IEEE2022

Mapping forest in the Swiss Alps treeline ecotone with explainable deep learning

Devis Tuia, Benjamin Alexander Kellenberger, Thiên-Anh Claris Nguyen

Forest maps are essential to understand forest dynamics. Due to the increasing availability of remote sensing data and machine learning models like convolutional neural networks, forest maps can these days be created on large scales with high accuracy. Com ...

Elsevier2022

LSSANet: A Long Short Slice-Aware Network for Pulmonary Nodule Detection

Jiancheng Yang, Bo Du, Rui Xu

Convolutional neural networks (CNNs) have been demonstrated to be highly effective in the field of pulmonary nodule detection. However, existing CNN based pulmonary nodule detection methods lack the ability to capture long-range dependencies, which is vita ...

SPRINGER INTERNATIONAL PUBLISHING AG2022

Robust Unsupervised Gaze Calibration Using Conversation and Manipulation Attention Priors

Jean-Marc Odobez, Rémy Alain Siegfried

Gaze estimation is a difficult task, even for humans. However, as humans, we are good at understanding a situation and exploiting it to guess the expected visual focus of attention of people, and we usually use this information to retrieve people's gaze. I ...

ASSOC COMPUTING MACHINERY2022

Uncertainty-aware Joint Salient Object and Camouflaged Object Detection

Tong Zhang

Visual salient object detection (SOD) aims at finding the salient object(s) that attract human attention, while camouflaged object detection (COD) on the contrary intends to discover the camouflaged object(s) that hidden in the surrounding. In this paper, ...

IEEE COMPUTER SOC2021

Spatial and temporal integration of visual features

Oh-Hyeon Choung

Visual processing can be seen as the integration and segmentation of features. Objects are composed of contours, integrated into shapes and segmented from other contours. Information also needs to be integrated to solve the ill-posed problems of vision. Fo ...

EPFL2021

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

Feed-forward and noise-tolerant detection of feature homogeneity in spiking networks with a latency code

Marc-Oliver Gewaltig

In studies of the visual system as well as in computer vision, the focus is often on contrast edges. However, the primate visual system contains a large number of cells that are insensitive to spatial contrast and, instead, respond to uniform homogeneous i ...

SPRINGER2021

Global 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 ...

2021

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