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Article . 2022
License: CC BY
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Article . 2022
License: CC BY
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ITI-CERTH participation in ActEV and AVS Tracks of TRECVID 2021

Authors: Gkountakos, Konstantinos; Galanopoulos, Damianos; Touska, Despoina; Ioannidis, Konstantinos; Vrochidis, Stefanos; Mezaris, Vasileios; Kompatsiaris, Ioannis;

ITI-CERTH participation in ActEV and AVS Tracks of TRECVID 2021

Abstract

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.

Keywords

Activity recognition, Activity detection, 3D-convolutional neural networks

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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