publication . Conference object . 2019

Incorporating Textual Similarity in Video Captioning Schemes

Gkountakos, Konstantinos; Dimou, Anastasios; Papadopoulos, Georgios Th.; Daras, Petros;
  • Published: 12 Aug 2019
  • Publisher: IEEE
The problem of video captioning has been heavily investigated from the research community the last years and, especially, since Recurrent Neural Networks (RNNs) have been introduced. Aforementioned approaches of video captioning, are usually based on sequence-to-sequence models that aim to exploit the visual information by detecting events, objects, or via matching entities to words. However, the exploitation of the contextual information that can be extracted from the vocabulary has not been investigated yet, except from approaches that make use of parts of speech such as verbs, nouns, and adjectives. The proposed approach is based on the assumption that textua...
free text keywords: Video captioning, Word2Vec, Textual information, Encoder-decoder, Visualization, Feature extraction, Closed captioning, Exploit, Computer science, Noun, Recurrent neural network, Artificial intelligence, business.industry, business, Vocabulary, media_common.quotation_subject, media_common, Part of speech, Natural language processing, computer.software_genre, computer
Funded by
Advanced tools for fighting oNline Illegal TrAfficking
  • Funder: European Commission (EC)
  • Project Code: 787061
  • Funding stream: H2020 | RIA
Digital Humanities and Cultural Heritage
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