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We introduce a novel framework for image captioning that can produce natural language explicitly grounded in entities that object detectors find in the image.
Long short-term memory
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Bleu: a method for automatic evaluation of machine translation
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Every picture tells a story: Generating sentences from images
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Babytalk: Understanding and generating simple image descriptions
G. Kulkarni, V. Premraj, V. Ordonez, S. Dhar, S. Li, Y. Choi, A. C. Berg, and T. L. Berg · 2011
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Collective generation of natural image descriptions
P. Kuznetsova, V. Ordonez, A. C. Berg, T. L. Berg, and Y. Choi · 2012
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Midge: Generating image descriptions from computer vision detections
M. Mitchell, X. Han, J. Dodge, A. Mensch, A. Goyal, A. Berg, K. Yamaguchi, T. Berg, K. Stratos, and H. Daumé III · 2012
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Efficient estimation of word representations in vector space
T. Mikolov, K. Chen, G. Corrado, and J. Dean · 2013
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A fast and accurate dependency parser using neural networks
D. Chen and C. Manning · 2014
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Meteor universal: Language specific translation evaluation for any target language
M. Denkowski and A. Lavie · 2014
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Referitgame: Referring to objects in photographs of natural scenes
S. Kazemzadeh, V. Ordonez, M. Matten, and T. L. Berg · 2014
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Adam: A method for stochastic optimization
D. Kingma and J. Ba · 2014
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Multimodal neural language models
R. Kiros, R. Salakhutdinov, and R. S. Zemel · 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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The Stanford CoreNLP natural language processing toolkit
C. D. Manning, M. Surdeanu, J. Bauer, J. Finkel, S. J. Bethard, and D. McClosky · 2014
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Glove: Global vectors for word representation
J. Pennington, R. Socher, and C. Manning · 2014
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Very deep convolutional networks for large-scale image recognition
K. Simonyan and A. Zisserman · 2014
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VQA: Visual Question Answering
S. Antol, A. Agrawal, J. Lu, M. Mitchell, D. Batra, C. L. Zitnick, and D. Parikh · 2015
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Mind’s eye: A recurrent visual representation for image caption generation
X. Chen and C. Lawrence Zitnick · 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
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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
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Deep visual-semantic alignments for generating image descriptions
A. Karpathy and L. Fei-Fei · 2015
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Deep captioning with multimodal recurrent neural networks (m-rnn)
J. Mao, W. Xu, Y. Yang, J. Wang, Z. Huang, and A. Yuille · 2015
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Flickr30k entities: Collecting region-to-phrase correspondences for richer image-to-sentence models
Densecap: Fully convolutional localization networks for dense captioning
J. Johnson, A. Karpathy, and L. Fei-Fei · 2016
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Generation and comprehension of unambiguous object descriptions
J. Mao, J. Huang, A. Toshev, O. Camburu, A. L. Yuille, and K. Murphy · 2016
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Grounding of textual phrases in images by reconstruction
A. Rohrbach, M. Rohrbach, R. Hu, T. Darrell, and B. Schiele · 2016
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Encode, review, and decode: Reviewer module for caption generation
Z. Yang, Y. Yuan, Y. Wu, R. Salakhutdinov, and W. W. Cohen · 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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Modeling context in referring expressions
L. Yu, P. Poirson, S. Yang, A. C. Berg, and T. L. Berg · 2016
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B. A. Plummer, L. Wang, C. M. Cervantes, J. C. Caicedo, J. Hockenmaier, and S. Lazebnik · 2015
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Faster r-cnn: Towards real-time object detection with region proposal networks
S. Ren, K. He, R. Girshick, and J. Sun · 2015
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Cider: Consensus-based image description evaluation
R. Vedantam, C. Lawrence Zitnick, and D. Parikh · 2015
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Pointer networks
O. Vinyals, M. Fortunato, and N. Jaitly · 2015
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Show and tell: A neural image caption generator
O. Vinyals, A. Toshev, S. Bengio, and D. Erhan · 2015
Cited alongside, same era.
Show, attend and tell: Neural image caption generation with visual attention
K. Xu, J. Ba, R. Kiros, K. Cho, A. Courville, R. Salakhutdinov, R. Zemel, and Y. Bengio · 2015
Cited alongside, same era.
Spice: Semantic propositional image caption evaluation
P. Anderson, B. Fernando, M. Johnson, and S. Gould · 2016
Cited alongside, same era.
Guided open vocabulary image captioning with constrained beam search
P. Anderson, B. Fernando, M. Johnson, and S. Gould · 2017
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Visual Dialog
A. Das, S. Kottur, K. Gupta, A. Singh, D. Yadav, J. M. Moura, D. Parikh, and D. Batra · 2017
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Mask r-cnn
K. He, G. Gkioxari, P. Dollár, and R. Girshick · 2017
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Knowing when to look: Adaptive attention via a visual sentinel for image captioning
J. Lu, C. Xiong, D. Parikh, and R. Socher · 2017
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Unofficial pytorch implementation for self-critical sequence training for image captioning
R. Luo · 2017
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Comprehension-guided referring expressions
R. Luo and G. Shakhnarovich · 2017
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Self-critical sequence training for image captioning
S. J. Rennie, E. Marcheret, Y. Mroueh, J. Ross, and V. Goel · 2017
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Captioning images with diverse objects
S. Venugopalan, L. A. Hendricks, M. Rohrbach, R. Mooney, T. Darrell, and K. Saenko · 2017
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A faster pytorch implementation of faster r-cnn
J. Yang, J. Lu, D. Batra, and D. Parikh · 2017
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Incorporating copying mechanism in image captioning for learning novel objects
T. Yao, Y. Pan, Y. Li, and T. Mei · 2017
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Bottom-up and top-down attention for image captioning and visual question answering
P. Anderson, X. He, C. Buehler, D. Teney, M. Johnson, S. Gould, and L. Zhang · 2018
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