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Recent large-scale text-driven synthesis models have attracted much attention thanks to their remarkable capabilities of generating highly diverse images that follow given text prompts.
Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 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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Deep unsupervised learning using nonequilibrium thermodynamics
Jascha Sohl-Dickstein, Eric Weiss, Niru Maheswaranathan, and Surya Ganguli · 2015
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Generative visual manipulation on the natural image manifold
Jun-Yan Zhu, Philipp Krähenbühl, Eli Shechtman, and Alexei A Efros · 2016
Earlier work this paper cites.
Fader networks: Manipulating images by sliding attributes
Guillaume Lample, Neil Zeghidour, Nicolas Usunier, Antoine Bordes, Ludovic Denoyer, and Marc’Aurelio Ranzato · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
Earlier work this paper cites.
Large scale gan training for high fidelity natural image synthesis
Andrew Brock, Jeff Donahue, and Karen Simonyan · 2018
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Photographic text-to-image synthesis with a hierarchically-nested adversarial network
Zizhao Zhang, Yuanpu Xie, and Lin Yang · 2018
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Image2stylegan: How to embed images into the stylegan latent space?
Rameen Abdal, Yipeng Qin, and Peter Wonka · 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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Controllable text-to-image generation
Bowen Li, Xiaojuan Qi, Thomas Lukasiewicz, and Philip Torr · 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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Learn, imagine and create: Text-to-image generation from prior knowledge
Tingting Qiao, Jing Zhang, Duanqing Xu, and Dacheng Tao · 2019
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Mirrorgan: Learning text-to-image generation by redescription
Tingting Qiao, Jing Zhang, Duanqing Xu, and Dacheng Tao · 2019
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Generative modeling by estimating gradients of the data distribution
Yang Song and Stefano Ermon · 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
Earlier work this paper cites.
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.
Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2020
Cited alongside, same era.
Df-gan: Deep fusion generative adversarial networks for text-to-image synthesis
Ming Tao, Hao Tang, Songsong Wu, Nicu Sebe, Xiao-Yuan Jing, Fei Wu, and Bingkun Bao · 2020
Cited alongside, same era.
In-domain gan inversion for real image editing
Jiapeng Zhu, Yujun Shen, Deli Zhao, and Bolei Zhou · 2020
Cited alongside, same era.
Clip2stylegan: Unsupervised extraction of stylegan edit directions
Rameen Abdal, Peihao Zhu, John Femiani, Niloy J Mitra, and Peter Wonka · 2021
Cited alongside, same era.
High-resolution image synthesis with latent diffusion models, 2021
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2021
Later among the works it cites.
Designing an encoder for stylegan image manipulation
Omer Tov, Yuval Alaluf, Yotam Nitzan, Or Patashnik, and Daniel Cohen-Or · 2021
Later among the works it cites.
High-fidelity gan inversion for image attribute editing
Tengfei Wang, Yong Zhang, Yanbo Fan, Jue Wang, and Qifeng Chen · 2021
Later among the works it cites.
Tedigan: Text-guided diverse face image generation and manipulation
Weihao Xia, Yujiu Yang, Jing-Hao Xue, and Baoyuan Wu · 2021
Later among the works it cites.
Gan inversion: A survey, 2021
Weihao Xia, Yulun Zhang, Yujiu Yang, Jing-Hao Xue, Bolei Zhou, and Ming-Hsuan Yang · 2021
Later among the works it cites.
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Paint by word, 2021
David Bau, Alex Andonian, Audrey Cui, YeonHwan Park, Ali Jahanian, Aude Oliva, and Antonio Torralba · 2021
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
Ming Ding, Zhuoyi Yang, Wenyi Hong, Wendi Zheng, Chang Zhou, Da Yin, Junyang Lin, Xu Zou, Zhou Shao, Hongxia Yang, et al · 2021
Cited alongside, same era.
Taming transformers for high-resolution image synthesis
Patrick Esser, Robin Rombach, and Bjorn Ommer · 2021
Cited alongside, same era.
Stylegan-nada: Clip-guided domain adaptation of image generators
Rinon Gal, Or Patashnik, Haggai Maron, Gal Chechik, and Daniel Cohen-Or · 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.
Hyperstyle: Stylegan inversion with hypernetworks for real image editing
Yuval Alaluf, Omer Tov, Ron Mokady, Rinon Gal, and Amit Bermano · 2022
Closest in time.
Omri Avrahami, Ohad Fried, and Dani Lischinski · 2022
Closest in time.
Blended diffusion for text-driven editing of natural images
Omri Avrahami, Dani Lischinski, and Ohad Fried · 2022
Closest in time.
Text2live: Text-driven layered image and video editing
Omer Bar-Tal, Dolev Ofri-Amar, Rafail Fridman, Yoni Kasten, and Tali Dekel · 2022
Closest in time.
Vqgan-clip: Open domain image generation and editing with natural language guidance
Katherine Crowson, Stella Biderman, Daniel Kornis, Dashiell Stander, Eric Hallahan, Louis Castricato, and Edward Raff · 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.
Diffusionclip: Text-guided diffusion models for robust image manipulation
Gwanghyun Kim, Taesung Kwon, and Jong Chul Ye · 2022
Closest in time.
Self-distilled stylegan: Towards generation from internet photos
Ron Mokady, Omer Tov, Michal Yarom, Oran Lang, Inbar Mosseri, Tali Dekel, Daniel Cohen-Or, and Michal Irani · 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.
Pivotal tuning for latent-based editing of real images
Daniel Roich, Ron Mokady, Amit H. Bermano, and Daniel Cohen-Or · 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, Tim Salimans, Tim Salimans, Jonathan Ho, David J Fleet, and Mohammad Norouzi · 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.