The 2020 ACM Transactions on Multimedia Computing, Communications and Applications (TOMM) Nicolas D. Georganas Best Paper Award is given to the paper “Increasing image memorability with neural style transfer” (TOMM vol. 15, Issue 2) by A. Siarohin, G. Zen, C. Majtanovic, X. Alameda-Pineda, E. Ricci, N. Sebe. The purpose of the named award is to recognize the most significant work in ACM TOMM (formerly TOMCCAP) in a given calendar year. The Associate Editors of ACM TOMM were invited to nominate articles which were published during calendar year 2019. Based on the nominations the winner has been chosen by the TOMM Editorial Board. The main assessment criteria have been quality, novelty, timeliness, clarity of presentation, in addition to relevance to multimedia computing, communications, and applications.

Recent works in computer vision and multimedia have shown that image memorability can be automatically inferred exploiting powerful deep-learning models. This article advances the state of the art in this area by addressing a novel and more challenging issue: “Given an arbitrary input image, can we make it more memorable?” To tackle this problem, authors introduced an approach based on an editing-by-applying- filters paradigm: given an input image, it is proposed to automatically retrieve a set of “style seeds,” i.e., a set of style images that, applied to the input image through a neural style transfer algorithm, provide the highest increase in memorability. It is shown the effectiveness of the proposed approach with experiments on the publicly available LaMem dataset, performing both a quantitative evaluation and a user study. To demonstrate the flexibility of the proposed framework, the impact of different implementation choices is also analyzed, such as using different state-of-the-art neural style transfer methods. Finally, several qualitative results are shown to provide additional insights on the link between image style and memorability.

The award honors the founding Editor-in-Chief of TOMM, Nicolas D. Georganas, for his outstanding contributions to the field of multimedia computing and his significant contributions to ACM. He exceedingly influenced the research and the whole multimedia community. The Editor-in-Chief Prof. Alberto Del Bimbo and the Editorial Board of ACM TOMM cordially congratulate the winner. The award will be presented to the authors at the ACM Multimedia 2020.

ABOUT THE AUTHORS

Aliaksandr Siarohin received the M.Sc. degree in computer science from the , in 2017. He is currently a PhD student in the Multimedia and Human Understanding Group at the University of Trento. His primary research focus is domain adaptation, image and video generation and generative adversarial networks.

Gloria Zen received the Ph.D. degree in computer science from the University of Trento, after Ph.D. internships in Microsoft Research in Seattle (WA), Xerox Research Center in Grenoble (France) and Yahoo! Research in New York City (NY). Her research interest is in computer vision and deep learning, with a focus on emotions and subjective cues. Before her PhD, she also worked for 4 years in a Machine Vision company and at Fondazione (FBK) in Trento, Italy. After working for over 12 years in IT, she moved to a different career path.

Cveta Majtanovic is both a psychologist and an industrial engineer, about to obtain a double Doctoral degree in Computer Science at Universities of and Trento. Apart from being a Lecturer and a Startup Mentor at University of Trento, Cveta is also committed to international business development of innovative startups and SMEs, with an extensive experience in research-to-commercialization activities and technology transfer operations in IT and Circular Economy domains. Her business-related and entrepreneurial competences have been awarded by the Italian Chamber of Commerce and Industry in UK, British Embassy in Italy, Italian Embassy in UK under the Young Italian Talents & Keynes Sraffa Award (2019). Cveta is member of the Board of Directors at the United Nations Global Compact Network Italy, Scientific Committee at European Cooperation in Science and Technology’s project GREENERING and Mentor of the Innovation Fund of R. Serbia, responsible for TRL evaluation and advances of new technologies towards full economic operation. Recently, she co-founded a groundbreaking AI-based startup “REENACT”, an innovative technology that allows machines to interpret human acting skills. Cveta’s research interests cover a range of topics at the intersection of computer vision and emotion recognition, along with human behavior and social media analysis.

Xavier Alameda-Pineda is a Research Scientist at Inria, in the Perception Group. He obtained the M.Sc. (equivalent) in Mathematics in 2008, in Telecommunications in 2009 from BarcelonaTech and in Computer Science in 2010 from Université Grenoble-Alpes (UGA). He then worked towards his Ph.D. in Mathematics and Computer Science, and obtained it 2013, from UGA. After a two-year post-doc period at the Multimodal Human Understanding Group, at University of Trento, he was appointed with his current position. Xavier is an active member of SIGMM, and a senior member of IEEE and a member of ELLIS. He is co-chairing the “Audio-visual machine perception and interaction for companion robots” chair of the Multidisciplinary Institute of Artificial Intelligence. Xavier is the Coordinator of the H2020 Project SPRING: Socially Pertinent Robots in Gerontological Healthcare. Xavier’s research interests are in combining machine learning, computer vision and audio processing for scene and behavior analysis and human-robot interaction.

Elisa Ricci is Associate Professor at the Department of Information Engineering and Computer Science (DISI) of the University of Trento (Italy) and the head of the Deep Visual Learning (DVL) unit at at Fondazione Bruno Kessler (FBK). Her research interests are directed to the development of deep learning algorithms and, in particular, of transfer learning and domain adaptation methods, with applications in the field of computer vision, multimedia analysis and robot perception. Elisa received her MSc (2004) and PhD degree (2008) in Electrical Engineering from the University of . Previously, she was an Assistant Professor at the University of Perugia (2011- 2017) and a researcher at the Idiap Research Institute (2009) and FBK (2010). She has been a visiting researcher at the Swiss Federal Institute of Technology and the University of Bristol. Elisa has co-authored more than 100 scientific publications and she regularly publishes in top-tier journals and conferences in computer vision and multimedia (CVPR/ICCV/NeurIPS/ACM MM, IEEE TPAMI, IJCV, IEEE TMM, IEEE TIP). She has received numerous awards for her scientific activity (Best paper award ACM MM 2015, INTEL Best Paper ICPR 2016, etc). She is/has been Program Chair of ACM MM 2020, Track Chair of ICPR 2020 and Area Chair of ACM MM 2016-2019, BMVC 2018-2020, ICCV 2017, ECCV 2018 and she regularly serves as reviewer for the major international conferences in computer vision and multimedia. She is/was the PI and/or participated to several national and international projects. Currently, she is the local coordinator of the EU H2020 project SPRING (2020-2023), where she leads research activities in multi-modal human behavior analysis for human robot interactions, and the EU H2020 project MARVEL (2020-2022), where she leads research activities in audio-visual surveillance.

Nicu Sebe is Professor with the University of Trento, Italy. He was the General Co-Chair of ACM Multimedia 2013, and the Program Chair of ACM Multimedia 2007and 2011, ICCV 2017 and ECCV 2016. He is a Program Chair of ICPR 2020 and ECCV 2024 and a general chair of ACM Multimedia 2022. He is a fellow of the International Association for Pattern Recognition and the vice-chair of ACM SIGMM. His main research interests relate to the investigation and implementation of new techniques in the fields of computer vision and multimedia. Specifically, in computer vision, he addresses a large spectrum of themes including human-behavior analysis, action recognition, 2D/3D object detection, large-scale event detection and video analysis, etc. In multimedia, his research focuses on three aspects: multimedia information retrieval, social signals processing and affective computing. The specific research topics include cross media retrieval, multi-modal learning, emotion recognition, multimodal brain-computer interfaces, etc.