English

Improving LSTM-based Video Description with Linguistic Knowledge Mined from Text

Computation and Language 2016-11-30 v2 Computer Vision and Pattern Recognition

Abstract

This paper investigates how linguistic knowledge mined from large text corpora can aid the generation of natural language descriptions of videos. Specifically, we integrate both a neural language model and distributional semantics trained on large text corpora into a recent LSTM-based architecture for video description. We evaluate our approach on a collection of Youtube videos as well as two large movie description datasets showing significant improvements in grammaticality while modestly improving descriptive quality.

Keywords

Cite

@article{arxiv.1604.01729,
  title  = {Improving LSTM-based Video Description with Linguistic Knowledge Mined from Text},
  author = {Subhashini Venugopalan and Lisa Anne Hendricks and Raymond Mooney and Kate Saenko},
  journal= {arXiv preprint arXiv:1604.01729},
  year   = {2016}
}

Comments

Accepted at EMNLP 2016. Project page: http://vsubhashini.github.io/language_fusion.html

R2 v1 2026-06-22T13:26:46.369Z