27 citations · 86 across the 23 of their papers we have counts for
12 papers · 1 filter
Contrastive Language-Image Pretrained Models are Zero-Shot Human Scanpath Predictors
Dario Zanca, Andrea Zugarini, Simon Dietz +4
Understanding the mechanisms underlying human attention is a fundamental challenge for both vision science and artificial intelligence. While numerous computational models of free-…
From Patches to Objects: Exploiting Spatial Reasoning for Better Visual Representations
Toni Albert, Bjoern Eskofier, Dario Zanca
As the field of deep learning steadily transitions from the realm of academic research to practical application, the significance of self-supervised pretraining methods has become…
Simulating Human Gaze with Neural Visual Attention
Leo Schwinn, Doina Precup, Bjoern Eskofier +1
Existing models of human visual attention are generally unable to incorporate direct task guidance and therefore cannot model an intent or goal when exploring a scene. To integrate…
Just a Matter of Scale? Reevaluating Scale Equivariance in Convolutional Neural Networks
Thomas Altstidl, An Nguyen, Leo Schwinn +4
The widespread success of convolutional neural networks may largely be attributed to their intrinsic property of translation equivariance. However, convolutions are not equivariant…
Behind the Machine's Gaze: Neural Networks with Biologically-inspired Constraints Exhibit Human-like Visual Attention
Leo Schwinn, Doina Precup, Björn Eskofier +1
By and large, existing computational models of visual attention tacitly assume perfect vision and full access to the stimulus and thereby deviate from foveated biological vision. M…
Don't Get Me Wrong: How to Apply Deep Visual Interpretations to Time Series
Christoffer Loeffler, Wei-Cheng Lai, Bjoern Eskofier +3
The correct interpretation of convolutional models is a hard problem for time series data. While saliency methods promise visual validation of predictions for image and language pr…
SVC-onGoing: Signature Verification Competition
Ruben Tolosana, Ruben Vera-Rodriguez, Carlos Gonzalez-Garcia +29
This article presents SVC-onGoing, an on-going competition for on-line signature verification where researchers can easily benchmark their systems against the state of the art in a…
ICDAR 2021 Competition on On-Line Signature Verification
Ruben Tolosana, Ruben Vera-Rodriguez, Carlos Gonzalez-Garcia +28
This paper describes the experimental framework and results of the ICDAR 2021 Competition on On-Line Signature Verification (SVC 2021). The goal of SVC 2021 is to evaluate the limi…
Gravitational Models Explain Shifts on Human Visual Attention
Dario Zanca, Marco Gori, Stefano Melacci +1
Visual attention refers to the human brain's ability to select relevant sensory information for preferential processing, improving performance in visual and cognitive tasks. It pro…
Wave Propagation of Visual Stimuli in Focus of Attention
Lapo Faggi, Alessandro Betti, Dario Zanca +2
Fast reactions to changes in the surrounding visual environment require efficient attention mechanisms to reallocate computational resources to most relevant locations in the visua…
Toward Improving the Evaluation of Visual Attention Models: a Crowdsourcing Approach
Dario Zanca, Stefano Melacci, Marco Gori
Human visual attention is a complex phenomenon. A computational modeling of this phenomenon must take into account where people look in order to evaluate which are the salient loca…
Visual Attention driven by Convolutional Features
Dario Zanca, Marco Gori
The understanding of where humans look in a scene is a problem of great interest in visual perception and computer vision. When eye-tracking devices are not a viable option, models…