Not logged in.
Quick Search - Contribution
Contribution Details
| Type | Conference or Workshop Paper |
| Scope | Discipline-based scholarship |
| Published in Proceedings | Yes |
| Title | A Multi-Stream Approach for Video Understanding |
| Organization Unit | |
| Authors |
|
| Presentation Type | paper |
| Item Subtype | Original Work |
| Refereed | Yes |
| Status | Published in final form |
| Language |
|
| ISBN | 9781450392037 |
| Page Range | 7003 - 7007 |
| 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 | The automatic annotation of higher-level semantic information in long-form video content is still a challenging task. The Deep Video Understanding (DVU) Challenge aims at catalyzing progress in this area by offering common data and tasks. In this paper, we present our contribution to the 3rd DVU challenge. Our approach consists of multiple information streams extracted from both the visual and the audio modality. The streams can build on information generated by previous streams to increase their semantic descriptiveness. Finally, the output of all streams can be aggregated in order to produce a graph representation of the input movie to represent the semantic relationships between the relevant characters. |
| Free access at | DOI |
| Official URL | https://dl.acm.org/doi/pdf/10.1145/3503161.3551567 |
| Related URLs | |
| Digital Object Identifier | 10.1145/3503161.3551567 |
| Other Identification Number | merlin-id:22814 |
| PDF File |
Download from ZORA
|
| Export |
BibTeX
EP3 XML (ZORA)
|