Conference paper Open Access

ITI-CERTH participation in TRECVID 2019

Konstantinos Gkountakos; Konstantinos Ioannidis; Stefanos Vrochidis; Ioannis Kompatsiaris


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{
  "inLanguage": {
    "alternateName": "eng", 
    "@type": "Language", 
    "name": "English"
  }, 
  "description": "<p>In this work, an overview of the submitted run to TRECVID 2019 by ITI-CERTH is presented and more specifically, for the task of Activities in Extended Video (ActEV). Towards this objective, we deployed a state-of-the-art architecture for the human action recognition problem and with the application of an encoder-decoder model, we extract a threshold for every activity in order for the framework not only to recognize activities but also to identify them in extended videos.</p>", 
  "license": "https://creativecommons.org/licenses/by/4.0/legalcode", 
  "creator": [
    {
      "affiliation": "Information Technologies Institute CERTH", 
      "@type": "Person", 
      "name": "Konstantinos Gkountakos"
    }, 
    {
      "affiliation": "Information Technologies Institute CERTH", 
      "@type": "Person", 
      "name": "Konstantinos Ioannidis"
    }, 
    {
      "affiliation": "Information Technologies Institute CERTH", 
      "@type": "Person", 
      "name": "Stefanos Vrochidis"
    }, 
    {
      "affiliation": "Information Technologies Institute CERTH", 
      "@type": "Person", 
      "name": "Ioannis Kompatsiaris"
    }
  ], 
  "headline": "ITI-CERTH participation in TRECVID 2019", 
  "image": "https://zenodo.org/static/img/logos/zenodo-gradient-round.svg", 
  "datePublished": "2020-03-01", 
  "url": "https://zenodo.org/record/4452098", 
  "@context": "https://schema.org/", 
  "identifier": "https://doi.org/10.5281/zenodo.4452098", 
  "@id": "https://doi.org/10.5281/zenodo.4452098", 
  "@type": "ScholarlyArticle", 
  "name": "ITI-CERTH participation in TRECVID 2019"
}
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