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Interactive video retrieval in the age of effective joint embedding deep models: lessons from the 11th VBS

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F23%3A10469914" target="_blank" >RIV/00216208:11320/23:10469914 - isvavai.cz</a>

  • Result on the web

    <a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=8uaHCF4xR8" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=8uaHCF4xR8</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/s00530-023-01143-5" target="_blank" >10.1007/s00530-023-01143-5</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Interactive video retrieval in the age of effective joint embedding deep models: lessons from the 11th VBS

  • Original language description

    This paper presents findings of the eleventh Video Browser Showdown competition, where sixteen teams competed in known-item and ad-hoc 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 high-level performance indicators are presented with overall statistics as well as in-depth analysis of the performance of selected tools implementing result set logging. The analysis reveals evidence that the CLIP model represents a versatile tool for cross-modal 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 ad-hoc search based tasks at Video Browser Showdown is introduced.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

    <a href="/en/project/GA22-21696S" target="_blank" >GA22-21696S: Deep Visual Representations of Unstructured Data</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2023

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Multimedia Systems

  • ISSN

    0942-4962

  • e-ISSN

    1432-1882

  • Volume of the periodical

    29

  • Issue of the periodical within the volume

    6

  • Country of publishing house

    DE - GERMANY

  • Number of pages

    24

  • Pages from-to

    3481-3504

  • UT code for WoS article

    001060126100001

  • EID of the result in the Scopus database

    2-s2.0-85168624324