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pro vyhledávání: '"Galanopoulos, Damianos"'
In this paper we tackle the cross-modal video retrieval problem and, more specifically, we focus on text-to-video retrieval. We investigate how to optimally combine multiple diverse textual and visual features into feature pairs that lead to generati
Externí odkaz:
http://arxiv.org/abs/2211.11351
Publikováno v:
Image and Vision Computing Journal, Elsevier, 2015
In this work we deal with the problem of high-level event detection in video. Specifically, we study the challenging problems of i) learning to detect video events from solely a textual description of the event, without using any positive video examp
Externí odkaz:
http://arxiv.org/abs/1511.08032
Akademický článek
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Publikováno v:
In Image and Vision Computing September 2016 53:35-44
Autor:
Gkountakos, Konstantinos, Galanopoulos, Damianos, Touska, Despoina, Ioannidis, Konstantinos, Vrochidis, Stefanos, Mezaris, Vasileios, Kompatsiaris, Ioannis
This report presents the overview of the runs related to Ad-hoc Video Search (AVS) and Activitiesin Extended Video (ActEV) tasks on behalf of the ITI-CERTH team. Our participation in the AVStask is based on a cross-modal deep network architecture uti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d21729e81993f344dbd5c8fbd2eeff1d
Matching images to articles is challenging and can be considered a special version of the cross-media retrieval problem. This working note paper presents our solution for the MediaEval NewsImages benchmarking task. We investigated the performance of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9d722f246f2107506a5f1f456f44f7f2
Autor:
Andreadis, Stelios, Moumtzidou, Anastasia, Galanopoulos, Damianos, Pantelidis, Nick, Apostolidis, Konstantinos, Touska, Despoina, Gkountakos, Konstantinos, Pegia, Maria, Gialampoukidis, Ilias, Vrochidis, Stefanos, Mezaris, Vasileios, Kompatsiaris, Ioannis
This paper presents VERGE, an interactive video search engine that integrates multiple retrieval methodologies and also combines them with reranking and fusion techniques. Moreover, a user interface, implemented as a Web application, enables users to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______2659::59b3805099412f1334ba0a68f988e776
https://zenodo.org/record/6656856
https://zenodo.org/record/6656856
This paper presents our team’s (IDT-ITI-CERTH) proposed method for the Visual Sentiment Analysis task of the Mediaeval 2021 benchmarking activity. Visual sentiment analysis is a challenging task as it involves a high level of subjectivity. The most
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::34f07ce5cefd505d2266eda9ea49f744
Autor:
Andreadis, Stelios, Moumtzidou, Anastasia, Gkountakos, Konstantinos, Pantelidis, Nick, Apostolidis, Konstantinos, Galanopoulos, Damianos, Gialampoukidis, Ilias, Vrochidis, Stefanos, Mezaris, Vasileios, Kompatsiaris, Ioannis
This paper presents VERGE, an interactive video search engine that supports efficient browsing and searching into a collection of images or videos. The framework involves a variety of retrieval approaches as well as reranking and fusion capabilities.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______2659::1bbb2257bce6cc29707b1ceafd7353c6
https://zenodo.org/record/4600835
https://zenodo.org/record/4600835
Autor:
Gkountakos, Konstantinos, Galanopoulos, Damianos, Mpakratsas, Marios, Touska, Despoina, Moumtzidou, Anastasia, Ioannidis, Konstantinos, Gialampoukidis, Ilias, Vrochidis, Stefanos, Mezaris, Vasileios, Kompatsiaris, Ioannis
This paper provides an overview of the runs submitted to TRECVID 2020 by ITI-CERTH. ITI-CERTH participated in the Ad-hoc Video Search (AVS), Disaster Scene Description and Indexing (DSDI) and Activities in Extended Video (ActEV) tasks. Our AVS task p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1a4304851360acdb24323bbb3efab441