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Generating a novel textual description of an image is an interesting problem that connects computer vision and natural language processing.
Gradient-based learning applied to document recognition
LeCun, Y., Bottou, L., Bengio, Y., and Haffner, P · 1998
Earlier work this paper cites.
BLEU: A Method for Automatic Evaluation of Machine Translation
Papineni, K., Roukos, S., Ward, T., and Zhu, W.-J · 2002
Earlier work this paper cites.
I2T: Image Parsing to Text Description
Yao, B. Z., Yang, X., Lin, L., Lee, M. W., and Zhu, S. C · 2010
Earlier work this paper cites.
Baby Talk: Understanding and Generating Simple Image Descriptions
Kulkarni, G., Premraj, V., Dhar, S., Li, Siming, Choi, Yejin, Berg, A. C., and Berg, T. L · 2011
Earlier work this paper cites.
Collective generation of natural image descriptions
Kuznetsova, P., Ordonez, V., Berg, A. C., Berg, T. L., and Choi, Y · 2012
Earlier work this paper cites.
Midge: Generating Image Descriptions from Computer Vision Detections
Mitchell, M., Han, X., Dodge, J., Mensch, A., Goyal, A., Berg, A., Yamaguchi, K., Berg, T., Stratos, K., and Daumé, III, H · 2012
Earlier work this paper cites.
Framing image description as a ranking task: data, models and evaluation metrics
Hodosh, M., Young, P., and Hockenmaier, J · 2013
Earlier work this paper cites.
Learning word embeddings efficiently with noise-contrastive estimation
Mnih, A. and Kavukcuoglu, Koray · 2013
Earlier work this paper cites.
Return of the Devil in the Details: Delving Deep into Convolutional Nets
Chatfield, K., Simonyan, K., Vedaldi, A., and Zisserman, A · 2014
Cited alongside, same era.
Learning a Recurrent Visual Representation for Image Caption Generation
Chen, X. and Zitnick, C. L · 2014
Cited alongside, same era.
Long-term Recurrent Convolutional Networks for Visual Recognition and Description
Donahue, J., Hendricks, L. A., Guadarrama, S., Rohrbach, M., Venugopalan, S., Saenko, K., and Darrell, T · 2014
Cited alongside, same era.
From Captions to Visual Concepts and Back
Fang, H., Gupta, S., Iandola, F. N., Srivastava, R., Deng, L., Dollár, P., Gao, J., He, X., Mitchell, M., Platt, J. C., Zitnick, C. L., and Zweig, G · 2014
Cited alongside, same era.
Deep Visual-Semantic Alignments for Generating Image Descriptions
Microsoft COCO: Common Objects in Context
Lin, T.-Y., Maire, M., Belongie, S., Hays, J., Perona, P., Ramanan, D., Dollár, P., and Zitnick, C. L · 2014
Later among the works it cites.
Explain Images with Multimodal Recurrent Neural Networks
Mao, J., Xu, W., Yang, Y., Wang, J., and Yuille, A. L · 2014
Later among the works it cites.
GloVe: Global Vectors for Word Representation
Pennington, J., Socher, R., and Manning, C. D · 2014
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Grounded Compositional Semantics for Finding and Describing Images with Sentences
Socher, R., Karpathy, A., Le, Q. V., Manning, C. D., and Ng, A. Y · 2014
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Multimodal Learning with Deep Boltzmann Machines
Srivastava, N. and Salakhutdinov, R · 2014
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Translating Videos to Natural Language Using Deep Recurrent Neural Networks
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Karpathy, A. and Fei-Fei, L · 2014
Cited alongside, same era.
Unifying Visual-Semantic Embeddings with Multimodal Neural Language Models
Kiros, R., Salakhutdinov, R., and Zemel, R. S · 2014
Cited alongside, same era.
Rehabilitation of Count-based Models for Word Vector Representations
Lebret, R. and Collobert, R · 2014
Cited alongside, same era.
Efficient Estimation of Word Representations in Vector Space
Mikolov, T., Chen, K., Corrado, G., and Dean, J
Cited in the paper.
Distributed Representations of Words and Phrases and their Compositionality
Mikolov, T., Sutskever, I., Chen, K., Corrado, G., and Dean, J
Cited in the paper.
Venugopalan, S., Xu, H., Donahue, J., Rohrbach, M., Mooney, R. J., and Saenko, K · 2014
Later among the works it cites.
Show and Tell: A Neural Image Caption Generator
Vinyals, O., Toshev, A., Bengio, S., and Erhan, D · 2014
Later among the works it cites.