Conference paper Open Access

ITI-CERTH participation in TRECVID 2020

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 participation is based on an attention-based cross-modal deep network method for retrieving video shots relevant to ad-hoc textual queries. The DSDI task is performed by implementing a multi-label image classification model, trained on all humanly annotated images and estimating the final classes on averaging the predictions on the keyframes of the video shots. For the ActEV task, we deploy an object detection algorithm and then convert the individual detected objects to activities by following an object tracking technique in order to detect human and vehicle-related activities.

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Publication date:
January 20, 2021
DOI:
10.5281/zenodo.4506490

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Grants:
European Commission:
  • ReTV - Enhancing and Re-Purposing TV Content for Trans-Vector Engagement (780656)
  • PREVISION - Prediction and Visual Intelligence for Security Information (833115)
  • aqua3S - Enhancing Standardisation strategies to integrate innovative technologies for Safety and Security in existing water networks (832876)
  • CONNEXIONs - InterCONnected NEXt-Generation Immersive IoT Platform of Crime and Terrorism DetectiON, PredictiON, InvestigatiON, and PreventiON Services (786731)
Meeting:
TRECVID 2020 Workshop, 2020
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License (for files):
Creative Commons Attribution 4.0 International

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