Automatic Description Generation from Images: A Survey of Models, Datasets, and Evaluation Measures

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10.1613:jair.4900.pdf

Date

2016-2-23

Author

Bernardi, Raffaella
Cakici, Ruket
Elliott, Desmond
Erdem, Aykut
Erdem, Erkut
Ikizler-Cinbis, Nazli
Keller, Frank
Muscat, Adrian
Plank, Barbara

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Automatic description generation from natural images is a challenging problem that has recently received a large amount of interest from the computer vision and natural language processing communities. In this survey, we classify the existing approaches based on how they conceptualize this problem, viz., models that cast description as either generation problem or as a retrieval problem over a visual or multimodal representational space. We provide a detailed review of existing models, highlighting their advantages and disadvantages. Moreover, we give an overview of the benchmark image datasets and the evaluation measures that have been developed to assess the quality of machine-generated image descriptions. Finally we extrapolate future directions in the area of automatic image description generation.

Subject Keywords

Artificial Intelligence

URI

https://hdl.handle.net/11511/51427

Journal

Journal of Artificial Intelligence Research

DOI

https://doi.org/10.1613/jair.4900

Collections

Department of Computer Engineering, Article

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Citation Formats

R. Bernardi et al., “Automatic Description Generation from Images: A Survey of Models, Datasets, and Evaluation Measures,” Journal of Artificial Intelligence Research, pp. 409–442, 2016, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/51427.