BMN: Boundary-Matching Network for Temporal Action Proposal Generation
Vision Technology (United States) · Baidu (China)
Abstract
Temporal action proposal generation is an challenging and promising task which aims to locate temporal regions in real-world videos where action or event may occur. Current bottom-up proposal generation methods can generate proposals with precise boundary, but cannot efficiently generate adequately reliable confidence scores for retrieving proposals. To address these difficulties, we introduce the Boundary-Matching (BM) mechanism to evaluate confidence scores of densely distributed proposals, which denote a proposal as a matching pair of starting and ending boundaries and combine all densely distributed BM pairs into the BM confidence map. Based on BM mechanism, we propose an effective, efficient and…
Citation impact
- FWCI
- 30.93
- Percentile
- 100%
- References
- 50
Authors
5- TLTianwei LinCorresponding
Vision Technology (United States), Baidu (China)
- XLXiao Liu
Baidu (China), Vision Technology (United States)
- XLXin Li
Vision Technology (United States), Baidu (China)
- EDErrui Ding
Vision Technology (United States), Baidu (China)
- SWShilei Wen
Baidu (China), Vision Technology (United States)
Topics & keywords
- Generalizability theory
- Computer science
- Classifier (UML)
- Matching (statistics)
- Boundary (topology)
- Artificial intelligence
- Task (project management)
- Action (physics)