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Interactive Video Retrieval in the Age of Deep Learning

Contributing authors of JOANNEUM RESEARCH:
Authors
Lokoc, Jakub; Schoefmann, Klaus; Bailer, Werner; Rossetto, Luca; Gurrin, Cathal
Abstract:
We present a tutorial focusing on video retrieval tasks, where state-of-the-art deep learning approaches still benefit from interactive decisions of users. The tutorial covers general introduction to the interactive video retrieval research area, state-of-the-art video retrieval systems, evaluation campaigns and recently observed results. Moreover, a significant part of the tutorial is dedicated to a practical exercise with three selected state-of-the-art systems in the form of an interactive video retrieval competition. Participants of this tutorial will gain a practical experience and also a general insight of the interactive video retrieval topic, which is a good start to focus their research on unsolved challenges in this area.
Title:
Interactive Video Retrieval in the Age of Deep Learning
Publikationsdatum
2019-06

Publikationsreihe

Adress
Ottawa, CA, Canada
Proceedings
ACM International Conference on Multimedia Retrieval
More files and links
Jahr/Monat:
2019

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