Exquisitor: Breaking the Interaction Barrier for Exploration of 100 Million Images
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| Publication date | 2019 |
| Book title | MM'19 |
| Book subtitle | proceedings of the 27th ACM Conference on Multimedia : October 21-25, 2019, Nice, France |
| ISBN (electronic) |
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| Event | 27th ACM International Conference on Multimedia, MM 2019 |
| Pages (from-to) | 1029-1031 |
| Publisher | New York, NY: Association for Computing Machinery |
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| Abstract | In this demonstration, we present Exquisitor, a media explorer capable of learning user preferences in real-time during interactions with the 99.2 million images of YFCC100M. Exquisitor owes its efficiency to innovations in data representation, compression, and indexing. Exquisitor can complete each interaction round, including learning preferences and presenting the most relevant results, in less than 30 ms using only a single CPU core and modest RAM. In short, Exquisitor can bring large-scale interactive learning to standard desktops and laptops, and even high-end mobile devices. |
| Document type | Conference contribution |
| Language | English |
| Published at | https://doi.org/10.1145/3343031.3350580 |
| Downloads |
3343031.3350580
(Final published version)
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