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We present an image caption system that addresses new challenges of automatically describing images in the wild.
Bleu: a method for automatic evaluation of machine translation
K. Papineni, S. Roukos, T. Ward, and W.-J. Zhu · 2002
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Re-evaluating the role of bleu in machine translation research
C. Callison-Burch and M. Osborne · 2006
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Meteor, m-bleu and m-ter: Evaluation metrics for high-correlation with human rankings of machine translation output
A. Agarwal and A. Lavie · 2008
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Freebase: a collaboratively created graph database for structuring human knowledge
K. Bollacker, C. Evans, P. Paritosh, T. Sturge, and J. Taylor · 2008
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Rectified linear units improve restricted boltzmann machines
V. Nair and G. E. Hinton · 2010
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Learning photographic global tonal adjustment with a database of input / output image pairs
V. Bychkovsky, S. Paris, E. Chan, and F. Durand · 2011
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Baby talk: Understanding and generating image descriptions
G. Kulkarni, V. Premraj, S. Dhar, S. Li, Y. Choi, A. C. Berg, and T. L. Berg · 2011
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Imagenet classification with deep convolutional neural networks
A. Krizhevsky, I. Sutskever, and G. E. Hinton · 2012
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Finding celebrities in billions of web images
X. Zhang, L. Zhang, X.-J. Wang, and H.-Y. Shum · 2012
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Learning deep structured semantic models for web search using clickthrough data
P.-S. Huang, X. He, J. Gao, L. Deng, A. Acero, and L. Heck · 2013
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Microsoft coco: Common objects in context
T.-Y. Lin, M. Maire, S. Belongie, J. Hays, P. Perona, D. Ramanan, P. Dollár, and C. L. Zitnick · 2014
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Microsoft COCO: Common objects in context
T.-Y. Lin, M. Maire, S. Belongie, J. Hays, P. Perona, D. Ramanan, P. Dollár, and C. L. Zitnick · 2014
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A latent semantic model with convolutional-pooling structure for information retrieval
Y. Shen, X. He, J. Gao, L. Deng, and G. Mesnil · 2014
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Very deep convolutional networks for large-scale image recognition
K. Simonyan and A. Zisserman · 2014
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Densecap: Fully convolutional localization networks for dense captioning
J. Johnson, A. Karpathy, and L. Fei-Fei · 2015
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Deep visual-semantic alignments for generating image descriptions
A. Karpathy and L. Fei-Fei · 2015
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ImageNet Large Scale Visual Recognition Challenge
O. Russakovsky, J. Deng, H. Su, J. Krause, S. Satheesh, S. Ma, Z. Huang, A. Karpathy, A. Khosla, M. Bernstein, A. C. Berg, and L. Fei-Fei · 2015
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Cider: Consensus-based image description evaluation
R. Vedantam, C. Lawrence Zitnick, and D. Parikh · 2015
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Show and tell: A neural image caption generator
O. Vinyals, A. Toshev, S. Bengio, and D. Erhan · 2015
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Show, attend and tell: Neural image caption generation with visual attention
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J. Devlin, H. Cheng, H. Fang, S. Gupta, L. Deng, X. He, G. Zweig, and M. Mitchell · 2015
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Long-term recurrent convolutional networks for visual recognition and description
J. Donahue, L. Anne Hendricks, S. Guadarrama, M. Rohrbach, S. Venugopalan, K. Saenko, and T. Darrell · 2015
Cited alongside, same era.
From captions to visual concepts and back
H. Fang, S. Gupta, F. Iandola, R. K. Srivastava, L. Deng, P. Dollár, J. Gao, X. He, M. Mitchell, J. C. Platt, et al · 2015
Cited alongside, same era.
Batch normalization: Accelerating deep network training by reducing internal covariate shift
S. Ioffe and C. Szegedy · 2015
Cited alongside, same era.
K. Xu, J. Ba, R. Kiros, A. Courville, R. Salakhutdinov, R. Zemel, and Y. Bengio · 2015
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Deep residual learning for image recognition
S. R. J. S. Kaiming He, Xiangyu Zhang · 2016
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Image captioning with semantic attention
Q. You, H. Jin, Z. Wang, C. Fang, and J. Luo · 2016
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