1 code implementation • 28 Feb 2024 • Giuseppe Cartella, Marcella Cornia, Vittorio Cuculo, Alessandro D'Amelio, Dario Zanca, Giuseppe Boccignone, Rita Cucchiara
Human attention modelling has proven, in recent years, to be particularly useful not only for understanding the cognitive processes underlying visual exploration, but also for providing support to artificial intelligence models that aim to solve problems in various domains, including image and video processing, vision-and-language applications, and language modelling.
no code implementations • 21 May 2023 • Dario Zanca, Andrea Zugarini, Simon Dietz, Thomas R. Altstidl, Mark A. Turban Ndjeuha, Leo Schwinn, Bjoern Eskofier
Understanding the mechanisms underlying human attention is a fundamental challenge for both vision science and artificial intelligence.
Ranked #1 on Scanpath prediction on CapMIT1003
no code implementations • 21 May 2023 • Toni Albert, Bjoern Eskofier, Dario Zanca
In this paper, we propose a novel auxiliary pretraining method that is based on spatial reasoning.
2 code implementations • 3 May 2023 • Kai Klede, Leo Schwinn, Dario Zanca, Björn Eskofier
Clustering is at the very core of machine learning, and its applications proliferate with the increasing availability of data.
no code implementations • 22 Nov 2022 • Leo Schwinn, Doina Precup, Bjoern Eskofier, Dario Zanca
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.
1 code implementation • 18 Nov 2022 • Thomas Altstidl, An Nguyen, Leo Schwinn, Franz Köferl, Christopher Mutschler, Björn Eskofier, Dario Zanca
We also demonstrate that our family of models is able to generalize well towards larger scales and improve scale equivariance.
no code implementations • 26 Jul 2022 • Christoffer Loeffler, Kion Fallah, Stefano Fenu, Dario Zanca, Bjoern Eskofier, Christopher John Rozell, Christopher Mutschler
We adapt an entropy-based active learning method with recent work from triplet mining to collect easy-to-answer but still informative annotations from human participants and use them to train a deep convolutional network that generalizes to unseen samples.
no code implementations • 19 May 2022 • Leo Schwinn, Leon Bungert, An Nguyen, René Raab, Falk Pulsmeyer, Doina Precup, Björn Eskofier, Dario Zanca
The reliability of neural networks is essential for their use in safety-critical applications.
no code implementations • 4 May 2022 • Sami Ede, Serop Baghdadlian, Leander Weber, An Nguyen, Dario Zanca, Wojciech Samek, Sebastian Lapuschkin
The ability to continuously process and retain new information like we do naturally as humans is a feat that is highly sought after when training neural networks.
no code implementations • 19 Apr 2022 • Leo Schwinn, Doina Precup, Björn Eskofier, Dario Zanca
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.
1 code implementation • 14 Mar 2022 • Christoffer Loeffler, Wei-Cheng Lai, Bjoern Eskofier, Dario Zanca, Lukas Schmidt, Christopher Mutschler
Explanatory visual interpretation approaches for image, and natural language processing allow domain experts to validate and understand almost any deep learning model.
no code implementations • 29 Sep 2021 • Christoffer Löffler, Wei-Cheng Lai, Lukas M Schmidt, Dario Zanca, Bjoern Eskofier, Christopher Mutschler
(Explanatory) visual interpretation approaches for image and natural language processing allow domain experts to validate and understand almost any deep learning model.
1 code implementation • 13 Aug 2021 • Ruben Tolosana, Ruben Vera-Rodriguez, Carlos Gonzalez-Garcia, Julian Fierrez, Aythami Morales, Javier Ortega-Garcia, Juan Carlos Ruiz-Garcia, Sergio Romero-Tapiador, Santiago Rengifo, Miguel Caruana, Jiajia Jiang, Songxuan Lai, Lianwen Jin, Yecheng Zhu, Javier Galbally, Moises Diaz, Miguel Angel Ferrer, Marta Gomez-Barrero, Ilya Hodashinsky, Konstantin Sarin, Artem Slezkin, Marina Bardamova, Mikhail Svetlakov, Mohammad Saleem, Cintia Lia Szucs, Bence Kovari, Falk Pulsmeyer, Mohamad Wehbi, Dario Zanca, Sumaiya Ahmad, Sarthak Mishra, Suraiya Jabin
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 an open common platform using large-scale public databases, such as DeepSignDB and SVC2021_EvalDB, and standard experimental protocols.
1 code implementation • 1 Jun 2021 • Ruben Tolosana, Ruben Vera-Rodriguez, Carlos Gonzalez-Garcia, Julian Fierrez, Santiago Rengifo, Aythami Morales, Javier Ortega-Garcia, Juan Carlos Ruiz-Garcia, Sergio Romero-Tapiador, Jiajia Jiang, Songxuan Lai, Lianwen Jin, Yecheng Zhu, Javier Galbally, Moises Diaz, Miguel Angel Ferrer, Marta Gomez-Barrero, Ilya Hodashinsky, Konstantin Sarin, Artem Slezkin, Marina Bardamova, Mikhail Svetlakov, Mohammad Saleem, Cintia Lia Szücs, Bence Kovari, Falk Pulsmeyer, Mohamad Wehbi, Dario Zanca, Sumaiya Ahmad, Sarthak Mishra, Suraiya Jabin
This paper describes the experimental framework and results of the ICDAR 2021 Competition on On-Line Signature Verification (SVC 2021).
no code implementations • 26 May 2021 • Mohamad Wehbi, Tim Hamann, Jens Barth, Peter Kaempf, Dario Zanca, Bjoern Eskofier
Most online handwriting recognition systems require the use of specific writing surfaces to extract positional data.
no code implementations • 21 May 2021 • Leo Schwinn, René Raab, An Nguyen, Dario Zanca, Bjoern Eskofier
Progress in making neural networks more robust against adversarial attacks is mostly marginal, despite the great efforts of the research community.
1 code implementation • 24 Feb 2021 • Leo Schwinn, An Nguyen, René Raab, Leon Bungert, Daniel Tenbrinck, Dario Zanca, Martin Burger, Bjoern Eskofier
The susceptibility of deep neural networks to untrustworthy predictions, including out-of-distribution (OOD) data and adversarial examples, still prevent their widespread use in safety-critical applications.
1 code implementation • 11 Jan 2021 • An Nguyen, Stefan Foerstel, Thomas Kittler, Andrey Kurzyukov, Leo Schwinn, Dario Zanca, Tobias Hipp, Da Jun Sun, Michael Schrapp, Eva Rothgang, Bjoern Eskofier
The overall framework is currently deployed, learns and evaluates predictive models from terabytes of IoT and enterprise data to actively monitor the customer sentiment for a fleet of thousands of high-end medical devices.
no code implementations • 5 Nov 2020 • Leo Schwinn, An Nguyen, René Raab, Dario Zanca, Bjoern Eskofier, Daniel Tenbrinck, Martin Burger
We empirically show that by incorporating this nonlocal gradient information, we are able to give a more accurate estimation of the global descent direction on noisy and non-convex loss surfaces.
no code implementations • 15 Sep 2020 • Dario Zanca, Marco Gori, Stefano Melacci, Alessandra Rufa
Another where the information from these maps is merged in order to select a single location to be attended for further and more complex computations and reasoning.
no code implementations • 19 Jun 2020 • Lapo Faggi, Alessandro Betti, Dario Zanca, Stefano Melacci, Marco Gori
Fast reactions to changes in the surrounding visual environment require efficient attention mechanisms to reallocate computational resources to most relevant locations in the visual field.
no code implementations • 11 Feb 2020 • Dario Zanca, Stefano Melacci, Marco Gori
A computational modeling of this phenomenon must take into account where people look in order to evaluate which are the salient locations (spatial distribution of the fixations), when they look in those locations to understand the temporal development of the exploration (temporal order of the fixations), and how they move from one location to another with respect to the dynamics of the scene and the mechanics of the eyes (dynamics).
no code implementations • 6 Feb 2020 • Dario Zanca, Alessandra Rufa
It is well known that a systematic analysis of the pupil size variations, recorded by means of an eye-tracker, is a rich source of information about a subject's arousal and cognitive state.
no code implementations • 3 Feb 2020 • Alessandro Rossi, Sara Ermini, Dario Bernabini, Dario Zanca, Marino Todisco, Alessandro Genovese, Antonio Rizzo
While theories postulating a dual cognitive system take hold, quantitative confirmations are still needed to understand and identify interactions between the two systems or conflict events.
no code implementations • ICLR 2019 • Giuseppe Marra, Dario Zanca, Alessandro Betti, Marco Gori
The effectiveness of deep neural architectures has been widely supported in terms of both experimental and foundational principles.
1 code implementation • 7 Feb 2018 • Dario Zanca, Valeria Serchi, Pietro Piu, Francesca Rosini, Alessandra Rufa
The second reason is the lack of sufficiently large and varied scanpath datasets.
1 code implementation • NeurIPS 2017 • Dario Zanca, Marco Gori
We devise variational laws of the eye-movement that rely on a generalized view of the Least Action Principle in physics.
Ranked #1 on Saliency Detection on CAT2000
1 code implementation • 10 Mar 2017 • Francesco Giannini, Vincenzo Laveglia, Alessandro Rossi, Dario Zanca, Andrea Zugarini
This report provides an introduction to some Machine Learning tools within the most common development environments.