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Contribution Details
Type | Conference or Workshop Paper |
Scope | Discipline-based scholarship |
Published in Proceedings | No |
Title | Open Challenges of Interactive Video Search and Evaluation |
Organization Unit | |
Authors |
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Presentation Type | lecture |
Item Subtype | Original Work |
Refereed | Yes |
Status | Published in final form |
Language |
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ISBN | 9781450392037 |
Page Range | 7383 - 7385 |
Event Title | MM '22: The 30th ACM International Conference on Multimedia |
Event Type | conference |
Event Location | Lisboa Portugal |
Event Start Date | November 10 - 2022 |
Event End Date | November 14 - 2022 |
Place of Publication | New York, NY, USA |
Publisher | ACM |
Abstract Text | During the last 10 years of Video Browser Showdown (VBS), there were many different approaches tested for known-item search and ad-hoc search tasks. Undoubtedly, teams incorporating state-of-the-art models from the machine learning domain had an advantage over teams focusing just on interactive interfaces. On the other hand, VBS results indicate that effective means of interaction with a search system is still necessary to accomplish challenging search tasks. In this tutorial, we summarize successful deep models tested at the Video Browser Showdown as well as interfaces designed on top of corresponding distance/similarity spaces. Our broad experience with competition organization and evaluation will be presented as well, focusing on promising findings and also challenging problems from the most recent iterations of the Video Browser Showdown. |
Free access at | DOI |
Official URL | https://dl.acm.org/doi/pdf/10.1145/3503161.3546973 |
Related URLs |
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Digital Object Identifier | 10.1145/3503161.3546973 |
Other Identification Number | merlin-id:22812 |
PDF File |
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