Publications and Conference Papers

E. Apostolidis, E. Adamantidou, A. Metsai, V. Mezaris, I. Patras, “Performance over Random: A robust evaluation protocol for video summarization methods“, Proc. ACM Multimedia 2020 (ACM MM), Seattle, WA, USA, Oct. 2020.

D. Galanopoulos, V. Mezaris, “Attention Mechanisms, Signal Encodings and Fusion Strategies for Improved Ad-hoc Video Search with Dual Encoding Networks“, Proc. ACM Int. Conf. on Multimedia Retrieval (ICMR 2020), Dublin, Ireland, 2020.

N. Gkalelis, V. Mezaris, “Fractional Step Discriminant Pruning: A Filter Pruning Framework for Deep Convolutional Neural Networks“, Proc. 7th IEEE Int. Workshop on Mobile Multimedia Computing (MMC2020) at the IEEE Int. Conf. on Multimedia and Expo (ICME), London, UK, July 2020.

Bocyte, R., Oomen, J., “Content Adaptation, Personalisation and Fine-grained Retrieval: Applying AI to Support Engagement with and Reuse of Archival Content at Scale“, Proc. 12th International Conference on Agents and Artificial Intelligence (ICAART 2020), vol. 1, pp. 506-511.

E. Apostolidis, E. Adamantidou, A. Metsai, V. Mezaris, I. Patras, “Unsupervised Video Summarization via Attention-Driven Adversarial Learning“, Proc. 26th Int. Conf. on Multimedia Modeling (MMM2020), Daejeon, Korea, Springer LNCS vol. 11961, pp. 492-504, Jan. 2020. Software available at https://github.com/e-apostolidis/SUM-GAN-AAE Best Paper Award

N. Gkalelis, V. Mezaris, “Subclass deep neural networks: re-enabling neglected classes in deep network training for multimedia classification“, Proc. 26th Int. Conf. on Multimedia Modeling (MMM2020), Daejeon, Korea, Springer LNCS vol. 11961, pp. 227-238, Jan. 2020. Software available at https://github.com/bmezaris/subclass_deep_neural_networks

Evlampios Apostolidis, Alexandros I. Metsai, Eleni Adamantidou, Vasileios Mezaris, and Ioannis Patras, “A Stepwise, Label-based Approach for Improving the Adversarial Training in Unsupervised Video Summarization”, in Proc. 1st Int. Workshop on AI for Smart TV Content Production, Access and Delivery (AI4TV ’19) at ACM Multimedia 2019, October 2019, Nice, France. Software available at https://github.com/e-apostolidis/SUM-GAN-sl

Basil Philipp, Krzysztof Ciesielski and Lyndon Nixon. “Automatically Adapting and Publishing TV Content for Increased Effectiveness and Efficiency“. in Proc. 1st Int. Workshop on AI for Smart TV Content Production, Access and Delivery (AI4TV ’19) at ACM Multimedia 2019, October 2019, Nice, France.

Lyndon Nixon, Krzysztof Ciesielski and Basil Philipp. “AI for Audience Prediction and Profiling to Power Innovative TV Content Recommendation Services“, in Proc. 1st Int. Workshop on AI for Smart TV Content Production, Access and Delivery (AI4TV ’19) at ACM Multimedia 2019, October 2019, Nice, France.

Weichselbraun, A., Brasoveanu, A., Kuntschik, P. and Nixon, L. (2019): “Improving Named Entity Linking Corpora Quality”. Poster at RANLP 2019, Varna, Bulgaria, September 2019.

J. Foss, B. Shirley, B. Malheiro, S. Kepplinger, L. Nixon, B. Philipp, V. Mezaris, A. Ulisses, “DataTV 2019: 1st International Workshop on Data Driven Personalisation of Television“, Proc. ACM Int. Conf. on Interactive Experiences for TV and Online Video (TVX 2019), Manchester, UK, June 2019.

Lyndon Nixon, Miggi Zwicklbauer, Lizzy Komen and Basil Philipp, “The Trans-Vector Platform for optimised Re-purposing and Re-publication of TV Content”,  DataTV workshop, at ACM TVX 2019, Manchester, UK, June 2019.

S. Andreadis, A. Moumtzidou, K. Apostolidis, K. Gkountakos, D. Galanopoulos, E. Michail, I. Gialampoukidis, S. Vrochidis, V. Mezaris, I. Kompatsiaris, “VERGE IN VBS 2020“, Proc. 26th Int. Conf. on Multimedia Modeling (MMM2020), Daejeon, Korea, Springer LNCS vol. 11962, pp 778-783, Jan. 2020.