FIAPR BMVA Distinguished Fellow 2015
School of Electronics and Computer Science University of Southampton UK
http://users.ecs.soton.ac.uk/msn/Link opens in a new window
Keynote talk: TBA
Mark S. Nixon is a Professor in the Vision, Learning and Control research group in the School of Electronics and Computer Science at the University of Southampton, UK. He was previously the President of the IEEE Biometrics Council and Vice Chair IEEE PSPB. He is a Fellow of the IAPR (for services to biometrics and computer vision) and the Distinguished Fellow of the BMVA 2015. His research interests are in image processing and computer vision and his team develops new techniques for static and moving shape extraction applied in medical image and behaviour analysis. He and his team were early workers in automatic face recognition, came to pioneer automatic gait recognition, helped to start ear biometrics and later soft biometrics for human identification. His books include Feature Extraction and Image Processing for Computer Vision (4th Ed. Academic Press 2019), Human ID Based on Gait (Springer 2005) and Doh! Fourier (World Scientific 2022). He has been chair/program co-chair for many conferences, especially biometrics ones, and given many invited talks.
Chair of the IEEE Information Forensics and Security Technical Committee
University Federico II of Naples, Italy
Keynote talk: Towards generalization in Deepfake detection
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, such as the well-known 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 effective 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.
Dr. 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 and in 2019-2020 she has been visiting scientist at Google AI in San Francisco. Her main contributions are in the area of multimedia forensics. She has published over 130 academic publications, including 50 journal papers. She has been technical Chair of the 2019 IEEE Workshop in Information Forensics and Security, general co-Chair of the 2019 ACM Workshop on Information Hiding and Multimedia Security and technical Chair of this same Workshop in 2021. She has been on the Editorial Board of IEEE Transactions on Information Forensics and Security and is currently Senior Associate Editor of IEEE Signal Processing Letters. Dr. Verdoliva is Chair of the IEEE Information Forensics and Security Technical Committee. She is the recipient of the 2018 Google Faculty Research Award and a TUM-IAS Hans Fischer Senior Fellowship. She is IEEE Fellow