Abstract
Integrating vision and language has long been a dream in work on artificial intelligence (AI). In the past two years, we have witnessed an explosion of work that brings together vision and language from images to videos and beyond. The available corpora have played a crucial role in advancing this area of research. In this paper, we propose a set of quality metrics for evaluating and analyzing the vision & language datasets and categorize them accordingly. Our analyses show that the most recent datasets have been using more complex language and more abstract concepts, however, there are different strengths and weaknesses in each.
Original language | English (US) |
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Title of host publication | Conference Proceedings - EMNLP 2015 |
Subtitle of host publication | Conference on Empirical Methods in Natural Language Processing |
Publisher | Association for Computational Linguistics (ACL) |
Pages | 207-213 |
Number of pages | 7 |
ISBN (Electronic) | 9781941643327 |
State | Published - Jan 1 2015 |
Event | Conference on Empirical Methods in Natural Language Processing, EMNLP 2015 - Lisbon, Portugal Duration: Sep 17 2015 → Sep 21 2015 |
Publication series
Name | Conference Proceedings - EMNLP 2015: Conference on Empirical Methods in Natural Language Processing |
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Other
Other | Conference on Empirical Methods in Natural Language Processing, EMNLP 2015 |
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Country | Portugal |
City | Lisbon |
Period | 9/17/15 → 9/21/15 |
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All Science Journal Classification (ASJC) codes
- Computational Theory and Mathematics
- Computer Science Applications
- Information Systems
Cite this
}
A survey of current datasets for vision and language research. / Ferraro, Francis; Mostafazadeh, Nasrin; Huang, Kenneth; Vanderwende, Lucy; Devlin, Jacob; Galley, Michel; Mitchell, Margaret.
Conference Proceedings - EMNLP 2015: Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics (ACL), 2015. p. 207-213 (Conference Proceedings - EMNLP 2015: Conference on Empirical Methods in Natural Language Processing).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - A survey of current datasets for vision and language research
AU - Ferraro, Francis
AU - Mostafazadeh, Nasrin
AU - Huang, Kenneth
AU - Vanderwende, Lucy
AU - Devlin, Jacob
AU - Galley, Michel
AU - Mitchell, Margaret
PY - 2015/1/1
Y1 - 2015/1/1
N2 - Integrating vision and language has long been a dream in work on artificial intelligence (AI). In the past two years, we have witnessed an explosion of work that brings together vision and language from images to videos and beyond. The available corpora have played a crucial role in advancing this area of research. In this paper, we propose a set of quality metrics for evaluating and analyzing the vision & language datasets and categorize them accordingly. Our analyses show that the most recent datasets have been using more complex language and more abstract concepts, however, there are different strengths and weaknesses in each.
AB - Integrating vision and language has long been a dream in work on artificial intelligence (AI). In the past two years, we have witnessed an explosion of work that brings together vision and language from images to videos and beyond. The available corpora have played a crucial role in advancing this area of research. In this paper, we propose a set of quality metrics for evaluating and analyzing the vision & language datasets and categorize them accordingly. Our analyses show that the most recent datasets have been using more complex language and more abstract concepts, however, there are different strengths and weaknesses in each.
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M3 - Conference contribution
AN - SCOPUS:84959904882
T3 - Conference Proceedings - EMNLP 2015: Conference on Empirical Methods in Natural Language Processing
SP - 207
EP - 213
BT - Conference Proceedings - EMNLP 2015
PB - Association for Computational Linguistics (ACL)
ER -