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Focusing on text-to-image (T2I) generation, we propose Text and Image Mutual-Translation Adversarial Networks (TIME), a lightweight but effective model that jointly learns a T2I generator G and an image captioning discriminator D under the Generative Adversarial Network framework.
Transformer-xl: Attentive language models beyond a fixed-length context
Dai, Z.; Yang, Z.; Yang, Y.; Carbonell, J.; Le, Q. V.; and Salakhutdinov, R. 2019 · 1901
Earlier work this paper cites.
The art of food: Meal image synthesis from ingredients
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Earlier work this paper cites.
Uniter: Learning universal image-text representations
Chen, Y.-C.; Li, L.; Yu, L.; Kholy, A. E.; Ahmed, F.; Gan, Z.; Cheng, Y.; and Liu, J. 2019 · 1909
Earlier work this paper cites.
Semantic Object Accuracy for Generative Text-to-Image Synthesis
Hinz, T.; Heinrich, S.; and Wermter, S. 2019 · 1910
Earlier work this paper cites.
Long short-term memory
Hochreiter, S.; and Schmidhuber, J. 1997 · 1997
Earlier work this paper cites.
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Mildenhall, B.; Srinivasan, P. P.; Tancik, M.; Barron, J. T.; Ramamoorthi, R.; and Ng, R. 2020 · 2003
Earlier work this paper cites.
X-Linear Attention Networks for Image Captioning
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Earlier work this paper cites.
Oscar: Object-semantics aligned pre-training for vision-language tasks
Li, X.; Yin, X.; Li, C.; Hu, X.; Zhang, P.; Zhang, L.; Wang, L.; Hu, H.; Dong, L.; Wei, F.; et al. 2020 · 2004
Earlier work this paper cites.
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Tay, Y.; Bahri, D.; Metzler, D.; Juan, D.-C.; Zhao, Z.; and Zheng, C. 2020 · 2005
Earlier work this paper cites.
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Deng, J.; Dong, W.; Socher, R.; Li, L.-J.; Li, K.; and Fei-Fei, L. 2009 · 2009
Earlier work this paper cites.
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Mikolov, T.; Karafiát, M.; Burget, L.; Černockỳ, J.; and Khudanpur, S. 2010 · 2010
Earlier work this paper cites.
Caltech-UCSD Birds 200
Welinder, P.; Branson, S.; Mita, T.; Wah, C.; Schroff, F.; Belongie, S.; and Perona, P. 2010 · 2010
Earlier work this paper cites.
Auto-encoding variational bayes
Kingma, D. P.; and Welling, M. 2013 · 2013
Earlier work this paper cites.
Generative adversarial nets
Goodfellow, I.; Pouget-Abadie, J.; Mirza, M.; Xu, B.; Warde-Farley, D.; Ozair, S.; Courville, A.; and Bengio, Y. 2014 · 2014
Earlier work this paper cites.
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 · 2014
Cited alongside, same era.
Conditional generative adversarial nets
Mirza, M.; and Osindero, S. 2014 · 2014
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Generating images from captions with attention
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Cited alongside, same era.
Generative adversarial text to image synthesis
Reed, S.; Akata, Z.; Yan, X.; Logeswaran, L.; Schiele, B.; and Lee, H. 2016 · 2016
Cited alongside, same era.
Improved techniques for training gans
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Cited alongside, same era.
Stackgan: Text to photo-realistic image synthesis with stacked generative adversarial networks
Zhang, H.; Xu, T.; Li, H.; Zhang, S.; Wang, X.; Huang, X.; and Metaxas, D. N. 2017 · 2017
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Bert: Pre-training of deep bidirectional transformers for language understanding
Devlin, J.; Chang, M.-W.; Lee, K.; and Toutanova, K. 2018 · 2018
Later among the works it cites.
Turbo learning for captionbot and drawingbot
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Which training methods for GANs do actually converge?
Mescheder, L.; Geiger, A.; and Nowozin, S. 2018 · 2018
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Attngan: Fine-grained text to image generation with attentional generative adversarial networks
Xu, T.; Zhang, P.; Huang, Q.; Zhang, H.; Gan, Z.; Huang, X.; and He, X. 2018 · 2018
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Conditional image generation with pixelcnn decoders
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Cited alongside, same era.
Gans trained by a two time-scale update rule converge to a local nash equilibrium
Heusel, M.; Ramsauer, H.; Unterthiner, T.; Nessler, B.; and Hochreiter, S. 2017 · 2017
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Lim, J. H.; and Ye, J. C. 2017 · 2017
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Parallel multiscale autoregressive density estimation
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Self-attention generative adversarial networks
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Dualattn-GAN: Text to Image Synthesis With Dual Attentional Generative Adversarial Network
Cai, Y.; Wang, X.; Yu, Z.; Li, F.; Xu, P.; Li, Y.; and Li, L. 2019 · 2019
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A style-based generator architecture for generative adversarial networks
Karras, T.; Laine, S.; and Aila, T. 2019 · 2019
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Mirrorgan: Learning text-to-image generation by redescription
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Language models are unsupervised multitask learners
Radford, A.; Wu, J.; Child, R.; Luan, D.; Amodei, D.; and Sutskever, I. 2019 · 2019
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Semantics disentangling for text-to-image generation
Yin, G.; Liu, B.; Sheng, L.; Yu, N.; Wang, X.; and Shao, J. 2019 · 2019
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Dm-gan: Dynamic memory generative adversarial networks for text-to-image synthesis
Zhu, M.; Pan, P.; Chen, W.; and Yang, Y. 2019 · 2019
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Controllable Text-to-Image Generation
Li, B.; Qi, X.; Lukasiewicz, T.; and Torr, P. 2019a · 2073
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