Edinburgh Research Explorer

Canonical Correlation Inference for Mapping Abstract Scenes to Text

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Related Edinburgh Organisations

Open Access permissions


Original languageEnglish
Title of host publicationProceedings of the Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18)
PublisherAssociation for the Advancement of Artificial Intelligence
Number of pages8
ISBN (Electronic)2374-3468
ISBN (Print)978-1-57735-800-8
Publication statusE-pub ahead of print - 7 Dec 2018
EventThirty-Second AAAI Conference on Artificial Intelligence - Hilton New Orleans Riverside, New Orleans, United States
Duration: 2 Feb 20187 Feb 2018


ConferenceThirty-Second AAAI Conference on Artificial Intelligence
Abbreviated titleAAAI-18
CountryUnited States
CityNew Orleans
Internet address


We describe a technique for structured prediction, based on canonical correlation analysis. Our learning algorithm finds two projections for the input and the output spaces that aim at projecting a given input and its correct output into points close to each other. We demonstrate our technique on a language-vision problem, namely the problem of giving a textual description to an “abstract scene.”


Thirty-Second AAAI Conference on Artificial Intelligence


New Orleans, United States

Event: Conference

Download statistics

No data available

ID: 50776491