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1
Defoiling foiled image captions
Madhyastha, P.; Wang, J.K.; Specia, L.. - : Association for Computational Linguistics (ACL), 2018
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2
Object counts! Bringing explicit detections back into image captioning
Wang, J.K.; Madhyastha, P.; Specia, L.. - : Association for Computational Linguistics (ACL), 2018
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3
End-to-end image captioning exploits multimodal distributional similarity
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4
Sheffield MultiMT: Using Object Posterior Predictions for Multimodal Machine Translation
Madhyastha, P.; Wang, J.K.; Specia, L.. - : Association for Computational Linguistics, 2017
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5
Unraveling the Contribution of Image Captioning and Neural Machine Translation for Multimodal Machine Translation
Lala, C.; Madhyastha, P.; Wang, J.K.. - : De Gruyter Open, 2017
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6
General Overview of ImageCLEF at the CLEF 2016 Labs
Villegas, M.; Müller, H.; García Seco de Herrera, A.. - : Springer International Publishing, 2016
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7
Combining Geometric, Textual and Visual Features for Predicting Prepositions in Image Descriptions
Ramisa, A.; Wang, J.K.; Lu, Y.; Dellandrea, E.; Moreno-Noguer, F.; Gaizauskas, R.. - : Association for Computational Linguistics, 2015
Abstract: We investigate the role that geometric, textual and visual features play in the task of predicting a preposition that links two visual entities depicted in an image. The task is an important part of the subsequent process of generating image descriptions. We explore the prediction of prepositions for a pair of entities, both in the case when the labels of such entities are known and unknown. In all situations we found clear evidence that all three features contribute to the prediction task.
URL: http://eprints.whiterose.ac.uk/99022/7/emnlp2015.pdf
http://aclweb.org/anthology/D15-1022
http://eprints.whiterose.ac.uk/99022/
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8
Generating Image Descriptions with Gold Standard Visual Inputs: Motivation, Evaluation and Baselines
Wang, J.K.; Gaizauskas, R.. - : Association for Computational Linguistics, 2015
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