"Research in videogames: use of deep learning for saliency estimation and cheating prevention”, Dr. Iuri Frosio (NVIDIA)
Dr. Iuri Frosio , PhD, NVIDIA USA
Seminar: Research in videogames: use of deep learning for saliency estimation and cheating prevention”

Abstract
Working in a company that is leader in both the videogames and machine learning fields offers exciting research opportunities at the intersection between these two domains. In this talk, I will illustrate two of these applications In the first part, I will concentrate my attention on saliency prediction in videogames, based on a dataset of Fortnite sequences that we acquired in 2019, I will illustrate the peculiar aspects of saliency in videogames, show that different frames in video sequences are not equally reliable, depending on the number of observers and frame content, and propose a general paradigm that explicitly takes this aspect into account when training a deep learning saliency prediction model. In the second part of the talk, I will introduce the problem of cheating in videogames and propose a deep learning based solution for the case of visual cheating. Our method allows identifying cheaters with high probability, and it is designed to be robust with respect to potential adversarial attacks put in place by cheat designers I will conclude the talk by illustrating other potential research areas including videogames and deep learning.

Wednesday 30th June, starting from 2pm.
The seminar will be held live from the Event Room of Technopole in Modena (Italy), street Vivarelli 2, 41125 (MO).

Due to limited seating, REGISTRATION IS REQUIRED.
Those who can attend the seminar will receive an email the day before (June 29th).
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