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Interactive Video Retrieval in the Age of Effective Joint Embedding Deep Models: Lessons from the 11th Vbs

Beteiligte Autor*innen der JOANNEUM RESEARCH:
Autor*innen:
Lokoč, Jakub and Andreadis, Stelios and Bailer, Werner and Duane, Aaron and Gurrin, Cathal and Ma, Zhixin and Messina, Nicola and Nguyen, ThaoNhu and Peška, Ladislav and Rossetto, Luca and Sauter, Loris and Schall, Konstantin and Schoeffmann, Klaus and Khan, Omar Shahbaz and Spiess, Florian and Vadicamo, Lucia and Vrochidis, Stefanos
Abstract:
This paper presents findings of the eleventh Video Browser Showdown competition, where sixteen teams competed in knownitem and adhoc search tasks. Many of the teams utilized state-of-the-art video retrieval approaches that demonstrated high effectiveness in challenging search scenarios. In this paper, a broad survey of all utilized approaches is presented in connection with an analysis of the performance of participating teams. Specifically, both highlevel performance indicators are presented with overall statistics as well as indepth analysis of the performance of selected tools implementing result set logging. The analysis reveals evidence that the CLIP model represents a versatile tool for crossmodal video retrieval when combined with interactive search capabilities. Furthermore, the analysis investigates the effect of different users and text query properties on the performance in search tasks. Last but not least, lessons learned from search task preparation are presented, and a new direction for adhoc search based tasks at Video Browser Showdown is introduced.
Titel:
Interactive Video Retrieval in the Age of Effective Joint Embedding Deep Models: Lessons from the 11th Vbs
Herausgeber (Verlag):
Springer Science and Business Media LLC
Seiten:
3481-3504

Publikationsreihe

Name
Multimedia Systems
Herausgeber(Verlag)
Springer Science and Business Media LLC
Nummer
29
ISSN
14321882

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