Conference paper Open Access
ITI-CERTH participation in ActEV and AVS Tracks of TRECVID 2021
Konstantinos Gkountakos;
Damianos Galanopoulos;
Despoina Touska;
Konstantinos Ioannidis;
Stefanos Vrochidis;
Vasileios Mezaris;
Ioannis Kompatsiaris
In this report, the overview of the runs during the TRECVID 2021 by the ITI-CERTH team are presented. ITI-CERTH participated in the Ad-hoc Video Search (AVS) and Activities in Extended Video (ActEV) tasks. For the AVS task, our participation is based on an attention-based cross-modal deep network architecture. As part of training this architecture, we experimented with a new hard negative
mining approach. For the ActEV task, we improve our framework, in terms of more accurate performance, by addressing the classification problem as multi-label rather than a single-label.
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- Publication date:
- March 1, 2022
- DOI:
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- Keyword(s):
- Activity detection Activity recognition 3D-convolutional neural networks
- Grants:
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European Commission:
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PREVISION - Prediction and Visual Intelligence for Security Information (833115)
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MIRROR - Migration-Related Risks caused by misconceptions of Opportunities and Requirement (832921)
- CONNEXIONs - InterCONnected NEXt-Generation Immersive IoT Platform of Crime and Terrorism DetectiON, PredictiON, InvestigatiON, and PreventiON Services (786731)
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PREVISION - Prediction and Visual Intelligence for Security Information (833115)
- Communities:
- License (for files):
- Creative Commons Attribution 4.0 International