Amato G, Bolettieri P, Carrara F, Falchi F, Gennaro C, Messina N, Vadicamo L, Vairo C
Video search Information search and retrieval Multi-modal retrieval Content-based video retrieval Surrogate text representation
In this paper, we present the fourth release of VISIONE, a tool for fast and effective video search on a large-scale dataset. It includes several search functionalities like text search, object and color-based search, semantic and visual similarity search, and temporal search. VISIONE uses ad-hoc textual encoding for indexing and searching video content, and it exploits a full-text search engine as search backend. In this new version of the system, we introduced some changes both to the current search techniques and to the user interface.
@inproceedings{oai:it.cnr:prodotti:486130, title = {VISIONE at Video Browser Showdown 2023}, author = {Amato G and Bolettieri P and Carrara F and Falchi F and Gennaro C and Messina N and Vadicamo L and Vairo C}, doi = {10.1007/978-3-031-27077-2_48}, year = {2023} }
Amato, Giuseppe0000-0003-0171-4315
Bolettieri, Paolo0000-0002-5225-4278
Carrara, Fabio0000-0001-5014-5089
Falchi, Fabrizio0000-0001-6258-5313
Gennaro, Claudio0000-0002-3715-149X
Messina, Nicola0000-0003-3011-2487
Vadicamo, Lucia0000-0001-7182-7038
Vairo, Claudio Francesco0000-0003-2740-4331
Artificial Intelligence for Media and Humanities (2021-ongoing)
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