Paper Info
Title
Visual Storytelling.
Abstract
We introduce the first dataset for sequential vision-to-language, and explore how this data may be used for the task of visual storytelling. The first release of this dataset, SIND v.1, includes 81,743 unique photos in 20,211 sequences, aligned to both descriptive (caption) and story language. We establish several strong baselines for the storytelling task, and motivate an automatic metric to benchmark progress. Modelling concrete description as well as figurative and social language, as provided in this dataset and the storytelling task, has the potential to move artificial intelligence from basic understandings of typical visual scenes towards more and more human-like understanding of grounded event structure and subjective expression.
Year
Venue
DocType
2016
HLT-NAACL
Conference
Volume
Citations 
PageRank 
abs/1604.03968
0
0.34
References 
Authors
0
15
Name
Order
Citations
PageRank
Ting-Hao Huang114619.23
Francis Ferraro2144.98
Nasrin Mostafazadeh3867.26
Ishan Misra420112.69
Aishwarya Agrawal536010.62
Jacob Devlin673832.34
Ross B. Girshick721921927.22
Xiaodong He83858190.28
Pushmeet Kohli97398332.84
Dhruv Batra102142104.81
C. Lawrence Zitnick117321332.72
Devi Parikh122929132.01
Lucy Vanderwende13105179.54
Michel Galley14215496.04
Margaret Mitchell15145065.37