CVAIApr 27, 2021

TRECVID 2020: A comprehensive campaign for evaluating video retrieval tasks across multiple application domains

arXiv:2104.13473v173 citations
Originality Synthesis-oriented
AI Analysis

It provides a standardized framework for benchmarking video retrieval systems, which is incremental as it builds on previous years' efforts.

The paper describes TRECVID 2020, an evaluation campaign that tackled video retrieval tasks across multiple domains, resulting in 29 teams participating in six tasks including ad-hoc video search and video summarization.

The TREC Video Retrieval Evaluation (TRECVID) is a TREC-style video analysis and retrieval evaluation with the goal of promoting progress in research and development of content-based exploitation and retrieval of information from digital video via open, metrics-based evaluation. Over the last twenty 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 2020 represented a continuation of four tasks and the addition of two new tasks. In total, 29 teams from various research organizations worldwide completed one or more of the following six tasks: 1. Ad-hoc Video Search (AVS), 2. Instance Search (INS), 3. Disaster Scene Description and Indexing (DSDI), 4. Video to Text Description (VTT), 5. Activities in Extended Video (ActEV), 6. Video Summarization (VSUM). This paper is an introduction to the evaluation framework, tasks, data, and measures used in the evaluation campaign.

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