  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.

Computer Vision and Pattern Recognition;Artificial Intelligence