ARC: Approximate Relevant Clip Query in Large-Scale Video Repositories
The exponential growth of video data highlights the necessity of exploring large-scale video repositories to extract valuable insights. Querying video clips based on content and temporal attributes is a critical task. However, existing solutions face two major challenges: insufficient flexibility in handling complex query conditions involving statistical reasoning and temporal constraints, and low efficiency under high query quality requirements and resource constraints.
Authors
- Xiaohui Yu (ORCID: https://orcid.org/0000-0001-8880-2304)
- Ziqiang Yu (ORCID: https://orcid.org/0000-0002-2836-9761)
- Zhenying He (ORCID: https://orcid.org/0000-0002-2926-4814)
- X. Sean Wang (ORCID: https://orcid.org/0000-0002-9059-3713)
- Yinan Jing (ORCID: https://orcid.org/0000-0002-1169-8032)
- Kai Zhang (ORCID: https://orcid.org/0000-0001-7518-5466)
- Yue Chen
Institutions
- Yantai University (CN)
- York University (CA)
- Fudan University (CN)
Publication Details
- Published
- 2025-07-13
- DOI
- https://doi.org/10.1145/3726302.3729896
- Primary Topic
- Video Analysis and Summarization
- Type
- article
- Field-Weighted Citation Impact
- 0.00