Amato G., Bolettieri P., Falchi F., Gennaro C., Messina N., Vadicamo L., Vairo C.
Deep learning Content based image retrieval Video retrieval Content-Based Video Retrieval Surrogate Text Representation VBS challenge CBIR Video Search Information Search and Retrieval Large scale information retrieval
This paper presents the second release of VISIONE, a tool for effective video search on large-scale collections. It allows users to search for videos using textual descriptions, keywords, occurrence of objects and their spatial relationships, occurrence of colors and their spatial relationships, and image similarity. One of the main features of our system is that it employs specially designed textual encodings for indexing and searching video content using the mature and scalable Apache Lucene full-text search engine.
Source: MMM 2021 - 27th International Conference on Multimedia Modeling, pp. 473–478, Prague, Czech Republic, 22-24/06/2021
@inproceedings{oai:it.cnr:prodotti:454281, title = {VISIONE at Video Browser Showdown 2021}, author = {Amato G. and Bolettieri P. and Falchi F. and Gennaro C. and Messina N. and Vadicamo L. and Vairo C.}, doi = {10.1007/978-3-030-67835-7_47}, booktitle = {MMM 2021 - 27th International Conference on Multimedia Modeling, pp. 473–478, Prague, Czech Republic, 22-24/06/2021}, year = {2021} }
Amato, Giuseppe0000-0003-0171-4315
Bolettieri, Paolo0000-0002-5225-4278
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)