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Text-to-image generation models have progressed considerably in recent years, which can now generate impressive realistic images from arbitrary text.
The md5 message-digest algorithm
Ronald Rivest · 1992
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Security analysis of sha-256 and sisters
Henri Gilbert and Helena Handschuh · 2003
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The Caltech-UCSD Birds-200-2011 Dataset
C. Wah, S. Branson, P. Welinder, P. Perona, and S. Belongie · 2011
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Birdsnap: Large-scale fine-grained visual categorization of birds
Thomas Berg, Jiongxin Liu, Seung Woo Lee, Michelle L. Alexander, David W. Jacobs, and Peter N. Belhumeur · 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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U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
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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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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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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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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2019
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A style-based generator architecture for generative adversarial networks
Tero Karras, Samuli Laine, and Timo Aila · 2019
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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
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Pytorch: An imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, et al · 2019
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Dm-gan: Dynamic memory generative adversarial networks for text-to-image synthesis
Minfeng Zhu, Pingbo Pan, Wei Chen, and Yi Yang · 2019
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Semantic object accuracy for generative text-to-image synthesis
Tobias Hinz, Stefan Heinrich, and Stefan Wermter · 2020
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
Cited alongside, same era.
Training generative adversarial networks with limited data
Tero Karras, Miika Aittala, Janne Hellsten, Samuli Laine, Jaakko Lehtinen, and Timo Aila · 2020
Cited alongside, same era.
Analyzing and improving the image quality of stylegan
Tero Karras, Samuli Laine, Miika Aittala, Janne Hellsten, Jaakko Lehtinen, and Timo Aila · 2020
Cited alongside, same era.
Freeze the discriminator: a simple baseline for fine-tuning gans
Sangwoo Mo, Minsu Cho, and Jinwoo Shin · 2020
Cited alongside, same era.
Connecting vision and language with localized narratives
Jordi Pont-Tuset, Jasper Uijlings, Soravit Changpinyo, Radu Soricut, and Vittorio Ferrari · 2020
Cited alongside, same era.
Denoising diffusion implicit models
Zero-shot text-to-image generation
Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray, Chelsea Voss, Alec Radford, Mark Chen, and Ilya Sutskever · 2021
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High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2021
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Df-gan: Deep fusion generative adversarial networks for text-to-image synthesis, 2021
Ming Tao, Hao Tang, Songsong Wu, Nicu Sebe, Xiao-Yuan Jing, Fei Wu, and Bingkun Bao · 2021
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Stylespace analysis: Disentangled controls for stylegan image generation
Zongze Wu, Dani Lischinski, and Eli Shechtman · 2021
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Tedigan: Text-guided diverse face image generation and manipulation
Weihao Xia, Yujiu Yang, Jing-Hao Xue, and Baoyuan Wu · 2021
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Jiaming Song, Chenlin Meng, and Stefano Ermon · 2020
Cited alongside, same era.
On leveraging pretrained gans for generation with limited data
Miaoyun Zhao, Yulai Cong, and Lawrence Carin · 2020
Cited alongside, same era.
Differentiable augmentation for data-efficient gan training
Shengyu Zhao, Zhijian Liu, Ji Lin, Jun-Yan Zhu, and Song Han · 2020
Cited alongside, same era.
Diffusion models beat gans on image synthesis
Prafulla Dhariwal and Alexander Nichol · 2021
Cited alongside, same era.
Cogview: Mastering text-to-image generation via transformers, 2021
Ming Ding, Zhuoyi Yang, Wenyi Hong, Wendi Zheng, Chang Zhou, Da Yin, Junyang Lin, Xu Zou, Zhou Shao, Hongxia Yang, and Jie Tang · 2021
Cited alongside, same era.
Classifier-free diffusion guidance
Jonathan Ho and Tim Salimans · 2021
Cited alongside, same era.
Alias-free generative adversarial networks
Tero Karras, Miika Aittala, Samuli Laine, Erik Härkönen, Janne Hellsten, Jaakko Lehtinen, and Timo Aila · 2021
Cited alongside, same era.
Cross-modal contrastive learning for text-to-image generation, 2021
Han Zhang, Jing Yu Koh, Jason Baldridge, Honglak Lee, and Yinfei Yang · 2021
Later among the works it cites.
Lafite: Towards language-free training for text-to-image generation
Yufan Zhou, Ruiyi Zhang, Changyou Chen, Chunyuan Li, Chris Tensmeyer, Tong Yu, Jiuxiang Gu, Jinhui Xu, and Tong Sun · 2021
Later among the works it cites.
Knn-diffusion: Image generation via large-scale retrieval
Oron Ashual, Shelly Sheynin, Adam Polyak, Uriel Singer, Oran Gafni, Eliya Nachmani, and Yaniv Taigman · 2022
Closest in time.
Re-imagen: Retrieval-augmented text-to-image generator
Wenhu Chen, Hexiang Hu, Chitwan Saharia, and William W Cohen · 2022
Closest in time.
Make-a-scene: Scene-based text-to-image generation with human priors
Oran Gafni, Adam Polyak, Oron Ashual, Shelly Sheynin, Devi Parikh, and Yaniv Taigman · 2022
Closest in time.
Mind the gap: Understanding the modality gap in multi-modal contrastive representation learning
Weixin Liang, Yuhui Zhang, Yongchan Kwon, Serena Yeung, and James Zou · 2022
Closest in time.
Hierarchical text-conditional image generation with clip latents
Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, and Mark Chen · 2022
Closest in time.
Photorealistic text-to-image diffusion models with deep language understanding
Chitwan Saharia, William Chan, Saurabh Saxena, Lala Li, Jay Whang, Emily Denton, Seyed Kamyar Seyed Ghasemipour, Burcu Karagol Ayan, S Sara Mahdavi, Rapha Gontijo Lopes, et al · 2022
Closest in time.
Scaling autoregressive models for content-rich text-to-image generation
Jiahui Yu, Yuanzhong Xu, Jing Yu Koh, Thang Luong, Gunjan Baid, Zirui Wang, Vijay Vasudevan, Alexander Ku, Yinfei Yang, Burcu Karagol Ayan, et al · 2022
Closest in time.