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Temporal Convolutional and Recurrent Networks for Image Captioning

  • Natalia IskraEmail author
  • Vitaly Iskra
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1055)

Abstract

Recently temporal convolutional networks have shown excellent qualities in sequence modeling tasks [1]. Taking this fact into account, in this paper we investigate the possibilities of replacing recurrent networks in architectures targeted specifically at image captioning. We evaluate the solution on Visual Genome dataset [2], which provides extensive set of labels and descriptions that thoroughly grounds visual concepts to natural language.

Keywords

Image captioning Convolutional neural networks Recurrent neural networks Visual Genome Dilated convolution Weight normalization Dropout Adam optimization 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Belarusian State University of Informatics and RadioelectronicsMinskRepublic of Belarus
  2. 2.Omnigon Communications LLCNew YorkUSA

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