Awad, G.
, Berns, F.
, Rossetto, L.
, Sch?ffmann, K.
and Beecks, C.
(2019),
V3C1 Dataset: An Evaluation of Content Characteristics, ACM International Conference on Multimedia Retrieval (ICMR), Ottawa, CA, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=927585 (Accessed October 22, 2026)
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V3C1 Dataset: An Evaluation of Content Characteristics
Published
Author(s)
, Fabian Berns, Luca Rossetto, Klaus Sch?ffmann, Christian Beecks
Abstract
In this work we analyze content statistics of the V3C1 dataset, which is the first partition of the Vimeo Creative Commons Collection (V3C). The dataset has been designed to represent true web videos in the wild, with good visual quality and diverse content characteristics, and will serve as evaluation basis for the Video Browser Showdown 2019-2021 and TRECVID Ad-Hoc Video Search tasks 2019-2021. The dataset comes with a shot segmentation (around 1 million shots) for which we analyze content specifics and statistics. %Such an evaluation is relevant for participants of TRECVID AVS or the VBS, as well as for colleagues using this dataset for any other research purpose. Our research will show that the content of V3C1 is very diverse, has no predominant characteristics and provides a low self-similarity. Thus it is very well suited for video retrieval evaluations as well as for participants of TRECVID AVS or the VBS.Proceedings Title
ACM International Conference on Multimedia Retrieval (ICMR)
Conference Dates
June 10-13, 2019
Conference Location
Ottawa, CA
Pub Type
Conferences
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Created June 5, 2019, Updated October 18, 2026