skip to main content

Explore Research Products in the NSF-PAR

  • Home
  • Search Results
  • Page 1 of 1

Search for: All records

Creators/Authors contains: "Licheng Yu, Hao Tan"

Note: When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher. Some full text articles may not yet be available without a charge during the embargo (administrative interval).
What is a DOI Number?

Some links on this page may take you to non-federal websites. Their policies may differ from this site.

  1. ( , IEEE Conference on Computer Vision and Pattern Recognition)
    Referring expressions are natural language construc- tions used to identify particular objects within a scene. In this paper, we propose a unified framework for the tasks of referring expression comprehension and generation. Our model is composed of three modules: speaker, listener, and reinforcer. The speaker generates referring expressions, the listener comprehends referring expressions, and the rein- forcer introduces a reward function to guide sampling of more discriminative expressions. The listener-speaker mod- ules are trained jointly in an end-to-end learning frame- work, allowing the modules to be aware of one another during learning while also benefiting from the discrimina- tive reinforcer’s feedback. We demonstrate that this unified framework and training achieves state-of-the-art results for both comprehension and generation on three referring ex- pression datasets. 
    more » « less
    Accepted Manuscript Full Text Available