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The Visual Dialogue task requires an agent to engage in a conversation about an image with a human.
Simple statistical gradient-following algorithms for connectionist reinforcement learning
R. J. Williams · 1992
Earlier work this paper cites.
Data-driven response generation in social media
A. Ritter, C. Cherry, and W. B. Dolan · 2011
Earlier work this paper cites.
Generative adversarial nets
I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, and Y. Bengio · 2014
Earlier work this paper cites.
Referit game: Referring to objects in photographs of natural scenes
S. Kazemzadeh, V. Ordonez, M. Matten, and T. L. Berg · 2014
Earlier work this paper cites.
Adam: A method for stochastic optimization
D. Kingma and J. Ba · 2014
Earlier work this paper cites.
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
Earlier work this paper cites.
Very deep convolutional networks for large-scale image recognition
K. Simonyan and A. Zisserman · 2014
Earlier work this paper cites.
Sequence to sequence learning with neural networks
I. Sutskever, O. Vinyals, and Q. V. Le · 2014
Earlier work this paper cites.
Show and tell: A neural image caption generator
O. Vinyals, A. Toshev, S. Bengio, and D. Erhan · 2014
Earlier work this paper cites.
VQA: Visual Question Answering
S. Antol, A. Agrawal, J. Lu, M. Mitchell, D. Batra, C. L. Zitnick, and D. Parikh · 2015
Earlier work this paper cites.
Deep generative image models using a laplacian pyramid of adversarial networks
E. L. Denton, S. Chintala, R. Fergus, et al · 2015
Earlier work this paper cites.
Deep visual-semantic alignments for generating image descriptions
A. Karpathy and L. Fei-Fei · 2015
Earlier work this paper cites.
Unsupervised representation learning with deep convolutional generative adversarial networks
A. Radford, L. Metz, and S. Chintala · 2015
Earlier work this paper cites.
Image Question Answering: A Visual Semantic Embedding Model and a New Dataset
M. Ren, R. Kiros, and R. Zemel · 2015
Earlier work this paper cites.
A neural network approach to context-sensitive generation of conversational responses
A. Sordoni, M. Galley, M. Auli, C. Brockett, Y. Ji, M. Mitchell, J.-Y. Nie, J. Gao, and B. Dolan · 2015
Earlier work this paper cites.
O. Vinyals and Q. Le · 2015
Cited alongside, same era.
Online sequence-to-sequence reinforcement learning for open-domain conversational agents
N. Asghar, P. Poupart, J. Xin, and H. Li · 2016
Cited alongside, same era.
Infogan: Interpretable representation learning by information maximizing generative adversarial nets
X. Chen, Y. Duan, R. Houthooft, J. Schulman, I. Sutskever, and P. Abbeel · 2016
Cited alongside, same era.
Natural language object retrieval
R. Hu, H. Xu, M. Rohrbach, J. Feng, K. Saenko, and T. Darrell · 2016
Cited alongside, same era.
Professor forcing: A new algorithm for training recurrent networks
A. M. Lamb, A. G. A. P. GOYAL, Y. Zhang, S. Zhang, A. C. Courville, and Y. Bengio · 2016
Cited alongside, same era.
Modeling context in referring expressions
L. Yu, P. Poirson, S. Yang, A. C. Berg, and T. L. Berg · 2016
Later among the works it cites.
Stackgan: Text to photo-realistic image synthesis with stacked generative adversarial networks
H. Zhang, T. Xu, H. Li, S. Zhang, X. Huang, X. Wang, and D. Metaxas · 2016
Later among the works it cites.
Towards diverse and natural image descriptions via a conditional gan
B. Dai, D. Lin, R. Urtasun, and S. Fidler · 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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Learning cooperative visual dialog agents with deep reinforcement learning
A. Das, S. Kottur, J. M. Moura, S. Lee, and D. Batra · 2017
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J. Li, W. Monroe, A. Ritter, M. Galley, J. Gao, and D. Jurafsky · 2016
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Hierarchical question-image co-attention for visual question answering
J. Lu, J. Yang, D. Batra, and D. Parikh · 2016
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Improved techniques for training gans
T. Salimans, I. Goodfellow, W. Zaremba, V. Cheung, A. Radford, and X. Chen · 2016
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Building end-to-end dialogue systems using generative hierarchical neural network models
I. V. Serban, A. Sordoni, Y. Bengio, A. C. Courville, and J. Pineau · 2016
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Continuously learning neural dialogue management
P.-H. Su, M. Gasic, N. Mrksic, L. Rojas-Barahona, S. Ultes, D. Vandyke, T.-H. Wen, and S. Young · 2016
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What Value Do Explicit High Level Concepts Have in Vision to Language Problems?
Q. Wu, C. Shen, A. v. d. Hengel, L. Liu, and A. Dick · 2016
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Ask Me Anything: Free-form Visual Question Answering Based on Knowledge from External Sources
Q. Wu, P. Wang, C. Shen, A. Dick, and A. v. d. Hengel · 2016
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H. de Vries, F. Strub, S. Chandar, O. Pietquin, H. Larochelle, and A. Courville · 2017
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Adversarial learning for neural dialogue generation
J. Li, W. Monroe, T. Shi, A. Ritter, and D. Jurafsky · 2017
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J. Lu, A. Kannan, J. Yang, D. Parikh, and D. Batra · 2017
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Image-grounded conversations: Multimodal context for natural question and response generation
N. Mostafazadeh, C. Brockett, B. Dolan, M. Galley, J. Gao, G. P. Spithourakis, and L. Vanderwende · 2017
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Visual reference resolution using attention memory for visual dialog
P. H. Seo, A. Lehrmann, B. Han, and L. Sigal · 2017
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A hierarchical latent variable encoder-decoder model for generating dialogues
I. V. Serban, A. Sordoni, R. Lowe, L. Charlin, J. Pineau, A. C. Courville, and Y. Bengio · 2017
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Speaking the same language: Matching machine to human captions by adversarial training
R. Shetty, M. Rohrbach, L. A. Hendricks, M. Fritz, and B. Schiele · 2017
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The vqa-machine: Learning how to use existing vision algorithms to answer new questions
P. Wang, Q. Wu, C. Shen, and A. v. d. Hengel · 2017
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Seqgan: Sequence generative adversarial nets with policy gradient
L. Yu, W. Zhang, J. Wang, and Y. Yu · 2017
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