Luisa Verdoliva
Università degli Studi di Napoli Federico II (Italy)
Deepfake Detection
Language: English
Date: October 29th / 10h45 – 12h00 (UTC-3)
Abstract
In recent years there have been astonishing advances in AI-based synthetic media generation. Thanks to deep learning-based approaches it is now possible to generate data with a high level of realism. While this opens up new opportunities for the entertainment industry, it simultaneously undermines the reliability of multimedia content and supports the spread of false or manipulated information on the Internet. This is especially true for human faces, allowing to easily create new identities or change only some specific attributes of a real face in a video, so-called deepfakes. In this context, it is important to develop automated tools to detect manipulated media in a reliable and timely manner. This talk will describe the most reliable deep learning-based approaches for detecting deepfakes, with a focus on those that enable domain generalization. The results will be presented on challenging datasets with reference to realistic scenarios, such as the dissemination of manipulated images and videos on social networks. Finally, new possible directions will be outlined.
Biography
Luisa Verdoliva is Associate Professor at University Federico II of Naples, Italy, where she leads the Multimedia Forensics Lab. In 2018 she has been visiting professor at Friedrich-Alexander-University (FAU) and in 2019-2020 she has been visiting scientist at Google AI in San Francisco. Her scientific interests are in the field of image and video processing, with main contributions in the area of multimedia forensics. She has published over 120 academic publications, including 45 journal papers. She is the PI for University Federico II of Naples in the DISCOVER (a Data-driven Integrated Approach for Semantic Inconsistencies Verification) project funded by DARPA under the SEMAFOR program (2020-2024). She has actively contributed to the academic community through service as technical Chair of the 2019 IEEE Workshop in Information Forensics and Security and the 2021 ACM Workshop on Information Hiding and Multimedia Security, area Chair of IEEE ICIP since 2017 and EUSIPCO since 2020. She has been also co-Chair of the IEEE CVPR Media Forensics Workshop both in 2020 and 2021. She is on the Editorial Board of IEEE Transactions on Information Forensics and Security and IEEE Signal Processing Letters and has been Guest Editor for IEEE Journal of Selected Topics in Signal Processing. Dr. Verdoliva is Chair of the IEEE Information Forensics and Security Technical Committee and vice-Chair of the EURASIP Signal and Data Analytics for Machine Learning Special Area Teams. She is the recipient of the 2018 Google Faculty Award for Machine Perception and a TUM-IAS Hans Fischer Senior Fellowship (2020-2023). She has been elected to the grade of IEEE Fellow since January 2021.