articleJun 1, 2016Closed access

Video Paragraph Captioning Using Hierarchical Recurrent Neural Networks

Purdue University West Lafayette · Baidu (China) · +1 more institution

Indexed incrossref

Abstract

We present an approach that exploits hierarchical Recurrent Neural Networks (RNNs) to tackle the video captioning problem, i.e., generating one or multiple sentences to describe a realistic video. Our hierarchical framework contains a sentence generator and a paragraph generator. The sentence generator produces one simple short sentence that describes a specific short video interval. It exploits both temporal-and spatial-attention mechanisms to selectively focus on visual elements during generation. The paragraph generator captures the inter-sentence dependency by taking as input the sentential embedding produced by the sentence generator, combining it with the paragraph history, and outputting the new initial…

Citation impact

559
total citations
FWCI
48.15
Percentile
100%
References
85
Citations per year

Authors

5

Topics & keywords

Keywords
  • Computer science
  • Sentence
  • Paragraph
  • Closed captioning
  • Generator (circuit theory)
  • Benchmark (surveying)
  • Artificial intelligence
  • Exploit
No related works found for this paper.

Funding