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The goal of text-to-image synthesis is to generate a visually realistic image that matches a given text description.
Bidirectional recurrent neural networks
Mike Schuster and Kuldip K Paliwal · 1997
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The caltech-ucsd birds-200-2011 dataset
Catherine Wah, Steve Branson, Peter Welinder, Pietro Perona, and Serge Belongie · 2011
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Generative adversarial nets
Ian J Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron C Courville, and Yoshua Bengio · 2014
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Microsoft coco: Common objects in context
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick · 2014
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Generative adversarial text to image synthesis
Scott Reed, Zeynep Akata, Xinchen Yan, Lajanugen Logeswaran, Bernt Schiele, and Honglak Lee · 2016
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Improved techniques for training gans
Tim Salimans, Ian Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, and Xi Chen · 2016
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Improved deep metric learning with multi-class n-pair loss objective
Kihyuk Sohn · 2016
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Rethinking the inception architecture for computer vision
Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe, Jon Shlens, and Zbigniew Wojna · 2016
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Learning deep structure-preserving image-text embeddings
Liwei Wang, Yin Li, and Svetlana Lazebnik · 2016
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Gans trained by a two time-scale update rule converge to a local nash equilibrium
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter · 2017
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Stackgan: Text to photo-realistic image synthesis with stacked generative adversarial networks
Han Zhang, Tao Xu, Hongsheng Li, Shaoting Zhang, Xiaogang Wang, Xiaolei Huang, and Dimitris N Metaxas · 2017
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Inferring semantic layout for hierarchical text-to-image synthesis
Seunghoon Hong, Dingdong Yang, Jongwook Choi, and Honglak Lee · 2018
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Image generation from scene graphs
Justin Johnson, Agrim Gupta, and Li Fei-Fei · 2018
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Unsupervised feature learning via non-parametric instance discrimination
Zhirong Wu, Yuanjun Xiong, Stella X Yu, and Dahua Lin · 2018
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Attngan: Fine-grained text to image generation with attentional generative adversarial networks
Tao Xu, Pengchuan Zhang, Qiuyuan Huang, Han Zhang, Zhe Gan, Xiaolei Huang, and Xiaodong He · 2018
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Stackgan++: Realistic image synthesis with stacked generative adversarial networks
Han Zhang, Tao Xu, Hongsheng Li, Shaoting Zhang, Xiaogang Wang, Xiaolei Huang, and Dimitris N Metaxas · 2018
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Photographic text-to-image synthesis with a hierarchically-nested adversarial network
Zizhao Zhang, Yuanpu Xie, and Lin Yang · 2018
Cited alongside, same era.
Adversarial learning of semantic relevance in text to image synthesis
Miriam Cha, Youngjune L Gwon, and HT Kung · 2019
Cited alongside, same era.
Tell, draw, and repeat: Generating and modifying images based on continual linguistic instruction
Alaaeldin El-Nouby, Shikhar Sharma, Hannes Schulz, Devon Hjelm, Layla El Asri, Samira Ebrahimi Kahou, Yoshua Bengio, and Graham W Taylor · 2019
Cited alongside, same era.
Generating multiple objects at spatially distinct locations
Tobias Hinz, Stefan Heinrich, and Stefan Wermter · 2019
Cited alongside, same era.
Controllable text-to-image generation
Bowen Li, Xiaojuan Qi, Thomas Lukasiewicz, and Philip Torr · 2019
Cited alongside, same era.
Rifegan: Rich feature generation for text-to-image synthesis from prior knowledge
Jun Cheng, Fuxiang Wu, Yanling Tian, Lei Wang, and Dapeng Tao · 2020
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Ching-Yao Chuang, Joshua Robinson, Lin Yen-Chen, Antonio Torralba, and Stefanie Jegelka · 2020
Later among the works it cites.
Contrastive multi-view representation learning on graphs
Kaveh Hassani and Amir Hosein Khasahmadi · 2020
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Momentum contrast for unsupervised visual representation learning
Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, and Ross Girshick · 2020
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Data-efficient image recognition with contrastive predictive coding
Olivier Henaff · 2020
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Object-driven text-to-image synthesis via adversarial training
Wenbo Li, Pengchuan Zhang, Lei Zhang, Qiuyuan Huang, Xiaodong He, Siwei Lyu, and Jianfeng Gao · 2019
Cited alongside, same era.
Learn, imagine and create: Text-to-image generation from prior knowledge
Tingting Qiao, Jing Zhang, Duanqing Xu, and Dacheng Tao · 2019
Cited alongside, same era.
Mirrorgan: Learning text-to-image generation by redescription
Tingting Qiao, Jing Zhang, Duanqing Xu, and Dacheng Tao · 2019
Cited alongside, same era.
A theoretical analysis of contrastive unsupervised representation learning
Nikunj Saunshi, Orestis Plevrakis, Sanjeev Arora, Mikhail Khodak, and Hrishikesh Khandeparkar · 2019
Cited alongside, same era.
Text2scene: Generating compositional scenes from textual descriptions
Fuwen Tan, Song Feng, and Vicente Ordonez · 2019
Cited alongside, same era.
Yonglong Tian, Dilip Krishnan, and Phillip Isola · 2019
Cited alongside, same era.
Fine-grained action retrieval through multiple parts-of-speech embeddings
Michael Wray, Diane Larlus, Gabriela Csurka, and Dima Damen · 2019
Cited alongside, same era.
Yannis Kalantidis, Mert Bulent Sariyildiz, Noe Pion, Philippe Weinzaepfel, and Diane Larlus · 2020
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Supervised contrastive learning
Prannay Khosla, Piotr Teterwak, Chen Wang, Aaron Sarna, Yonglong Tian, Phillip Isola, Aaron Maschinot, Ce Liu, and Dilip Krishnan · 2020
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Cpgan: Content-parsing generative adversarial networks for text-to-image synthesis
Jiadong Liang, Wenjie Pei, and Feng Lu · 2020
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Self-supervised learning of pretext-invariant representations
Ishan Misra and Laurens van der Maaten · 2020
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Contrastive learning with hard negative samples
Joshua Robinson, Ching-Yao Chuang, Suvrit Sra, and Stefanie Jegelka · 2020
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Df-gan: Deep fusion generative adversarial networks for text-to-image synthesis
Ming Tao, Hao Tang, Songsong Wu, Nicu Sebe, Fei Wu, and Xiao-Yuan Jing · 2020
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What makes for good views for contrastive learning
Yonglong Tian, Chen Sun, Ben Poole, Dilip Krishnan, Cordelia Schmid, and Phillip Isola · 2020
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Retrievegan: Image synthesis via differentiable patch retrieval
Hung-Yu Tseng, Hsin-Ying Lee, Lu Jiang, Ming-Hsuan Yang, and Weilong Yang · 2020
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Understanding contrastive representation learning through alignment and uniformity on the hypersphere
Tongzhou Wang and Phillip Isola · 2020
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Zero-shot text-to-image generation
Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray, Chelsea Voss, Alec Radford, Mark Chen, and Ilya Sutskever · 2021
Closest in time.
Cross-modal contrastive learning for text-to-image generation
Han Zhang, Jing Yu Koh, Jason Baldridge, Honglak Lee, and Yinfei Yang · 2021
Closest in time.