Publications related to Modeling Object Dissimilarity for Deep Saliency Prediction

Related publications (23)

SVGC-AVA: 360-Degree Video Saliency Prediction With Spherical Vector-Based Graph Convolution and Audio-Visual Attention

Viewers of 360-degree videos are provided with both visual modality to characterize their surrounding views and audio modality to indicate the sound direction. Though both modalities are important for saliency prediction, little work has been done by joint ...

Ieee-Inst Electrical Electronics Engineers Inc2024

Match Normalization: Learning-Based Point Cloud Registration for 6D Object Pose Estimation in the Real World

Mathieu Salzmann, Zheng Dang

In this work, we tackle the task of estimating the 6D pose of an object from point cloud data. While recent learning-based approaches have shown remarkable success on synthetic datasets, we have observed them to fail in the presence of real-world data. We ...

Ieee Computer Soc2024

Decoding electroencephalographic responses to visual stimuli compatible with electrical stimulation

Silvestro Micera, Laura Toni, Fiorenzo Artoni, Simone Romeni

Electrical stimulation of the visual nervous system could improve the quality of life of patients affected by acquired blindness by restoring some visual sensations, but requires careful optimization of stimulation parameters to produce useful perceptions. ...

Aip Publishing2024

Temporal aspects of feature integration in vision

Lukas Vogelsang

To fully comprehend visual perception, we need to necessarily understand its temporal dimension. Our visual environment is highly dynamic, requiring the processing and integration of temporal signals in order to make sense of it. Many processes, such as th ...

EPFL2024

Saliency prediction in 360° architectural scenes: Performance and impact of daylight variations

Marilyne Andersen, Sabine Süsstrunk, Caroline Karmann, Kynthia Chamilothori, Seungryong Kim, Bahar Aydemir

Saliency models are image-based prediction models that estimate human visual attention. Such models, when applied to architectural spaces, could pave the way for design decisions where visual attention is taken into account. In this study, we tested the pe ...

2023

Towards Visual Saliency Explanations of Face Verification

Touradj Ebrahimi, Yuhang Lu

In the past years, deep convolutional neural networks have been pushing the frontier of face recognition (FR) techniques in both verification and identification scenarios. Despite the high accuracy, they are often criticized for lacking explainability. The ...

2024

Development of Visual Memory Capacity Following Early-Onset and Extended Blindness

Lukas Vogelsang

It is unknown whether visual memory capacity can develop if onset of pattern vision is delayed for several years following birth. We had an opportunity to address this question through our work with an unusual population of 12 congenitally blind individual ...

2022

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

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

Features integrate along a motion trajectory when object integrity is preserved

Michael Herzog, Leila Drissi Daoudi - Kleinbauer

Information about a moving object is usually poor at each retinotopic location because photoreceptor activation is short, noisy, and affected by shadows, reflections of other objects, and so on. Integration across the motion trajectory may yield a much bet ...

Association for Research in Vision and Ophthalmology (ARVO)2021

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 ...

Association for Research in Vision and Ophthalmology (ARVO)2021

Crowding and the Architecture of the Visual System

Adrien Christophe Doerig

Classically, vision is seen as a cascade of local, feedforward computations. This framework has been tremendously successful, inspiring a wide range of ground-breaking findings in neuroscience and computer vision. Recently, feedforward Convolutional Neural ...

EPFL2020

Long-lasting feature integration

Leila Drissi Daoudi - Kleinbauer

In the classic model of vision, processing is local, feedforward and hierarchical. The first stages of the visual system are retinotopic, i.e., neighboring points in the outside world are mapped onto neighboring photoreceptors of the retina and this is pre ...

EPFL2020

Visual Attention and Perceptual Quality in Omnidirectional Imaging

Evgeniy Upenik

Omnidirectional imaging has reached a level of widespread availability driven by recent advances in integrated circuit technology, image sensors, and computer graphics which allow now capturing, rendering and displaying of such type of immersive content in ...

EPFL2020

Towards Modelling of Visual Saliency in Point Clouds for Immersive Applications

Touradj Ebrahimi, Evangelos Alexiou

Modelling human visual attention is of great importance in the field of computer vision and has been widely explored for 3D imaging. Yet, in the absence of ground truth data, it is unclear whether such predictions are in alignment with the actual human vie ...

2019

Gene Editing Preserves Visual Functions in a Mouse Model of Retinal Degeneration

Diego Ghezzi, Naïg Aurelia Ludmilla Chenais, Paola Vagni

Inherited retinal dystrophies (IRDs) are a large and heterogeneous group of degenerative diseases caused by mutations in various genes. Given the favorable anatomical and immunological characteristics of the eye, gene therapy holds great potential for thei ...

2019

Schizophrenia patients using atypical medication perform better in visual tasks than patients using typical medication

Michael Herzog, Maya Roinishvili, Albulena Jashari-Shaqiri

Schizophrenia (SCZ) patients show deficits in many domains, including cognition and perception. However, results are often mixed. One reason for mixed results may be differences in medication. Very little is known about the role of medication in visual pro ...

2019

Running Large-Scale Simulations on the Neurorobotics Platform to Understand Vision - The Case of Visual Crowding

Michael Herzog, Gregory Francis, Alban Bornet

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

Optimal integration of intraneural somatosensory feedback with visual information: a single-case study

Silvestro Micera, Ivo Strauss, Giacomo Valle

Providing somatosensory feedback to amputees is a long-standing objective in prosthesis research. Recently, implantable neural interfaces have yielded promising results in this direction. There is now considerable evidence that the nervous system integrate ...

Nature Research2019