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TRECVID 2019: An Evaluation Campaign to Benchmark Video Activity Detection, Video Captioning and Matching, and Video Search & Retrieval
- Source :
- TREC Video Retrieval Evaluation: TRECVID, TREC Video Retrieval Evaluation: TRECVID, Nov 2019, Gaithersburg, United States, Scopus-Elsevier, 2019 TREC Video Retrieval Evaluation, TRECVID 2019, 2019 TREC Video Retrieval Evaluation, TRECVID 2019, 12 November 2019 through 13 November 2019
- Publication Year :
- 2020
- Publisher :
- arXiv, 2020.
-
Abstract
- The TREC Video Retrieval Evaluation (TRECVID) 2019 was a TREC-style video analysis and retrieval evaluation, the goal of which remains to promote progress in research and development of content-based exploitation and retrieval of information from digital video via open, metrics-based evaluation. Over the last nineteen years this effort has yielded a better understanding of how systems can effectively accomplish such processing and how one can reliably benchmark their performance. TRECVID has been funded by NIST (National Institute of Standards and Technology) and other US government agencies. In addition, many organizations and individuals worldwide contribute significant time and effort. TRECVID 2019 represented a continuation of four tasks from TRECVID 2018. In total, 27 teams from various research organizations worldwide completed one or more of the following four tasks: 1. Ad-hoc Video Search (AVS) 2. Instance Search (INS) 3. Activities in Extended Video (ActEV) 4. Video to Text Description (VTT) This paper is an introduction to the evaluation framework, tasks, data, and measures used in the workshop.<br />Comment: TRECVID Workshop overview paper. 39 pages
- Subjects :
- FOS: Computer and information sciences
Artificial Intelligence (cs.AI)
Computer Science - Artificial Intelligence
[INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR]
Computer Vision and Pattern Recognition (cs.CV)
Computer Science - Computer Vision and Pattern Recognition
[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]
ComputingMilieux_MISCELLANEOUS
[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- TREC Video Retrieval Evaluation: TRECVID, TREC Video Retrieval Evaluation: TRECVID, Nov 2019, Gaithersburg, United States, Scopus-Elsevier, 2019 TREC Video Retrieval Evaluation, TRECVID 2019, 2019 TREC Video Retrieval Evaluation, TRECVID 2019, 12 November 2019 through 13 November 2019
- Accession number :
- edsair.doi.dedup.....b214130a8f96a3c4106b5c7986d323b4
- Full Text :
- https://doi.org/10.48550/arxiv.2009.09984