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With the advance of diffusion models, various personalized image generation methods have been proposed.
Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2014
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Image style transfer using convolutional neural networks
Leon A. Gatys, Alexander S. Ecker, and Matthias Bethge · 2016
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Arbitrary style transfer in real-time with adaptive instance normalization
Xun Huang and Serge Belongie · 2017
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Deep laplacian pyramid networks for fast and accurate super-resolution
Wei-Sheng Lai, Jia-Bin Huang, Narendra Ahuja, and Ming-Hsuan Yang · 2017
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Demystifying neural style transfer
Yanghao Li, Naiyan Wang, Jiaying Liu, and Xiaodi Hou · 2017
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Universal style transfer via feature transforms
Yijun Li, Chen Fang, Jimei Yang, Zhaowen Wang, Xin Lu, and Ming-Hsuan Yang · 2017
Earlier work this paper cites.
A closed-form solution to photorealistic image stylization
Yijun Li, Ming-Yu Liu, Xueting Li, Ming-Hsuan Yang, and Jan Kautz · 2018
Earlier work this paper cites.
A closed-form solution to universal style transfer
Ming Lu, Hao Zhao, Anbang Yao, Yurong Chen, Feng Xu, and Li Zhang · 2019
Earlier work this paper cites.
Improved artgan for conditional synthesis of natural image and artwork
Wei Ren Tan, Chee Seng Chan, Hernán E. Aguirre, and Kiyoshi Tanaka · 2019
Earlier work this paper cites.
Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
Earlier work this paper cites.
Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2020
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Diffusion models beat gans on image synthesis
Prafulla Dhariwal and Alex Nichol · 2021
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Lora: Low-rank adaptation of large language models
J. Edward Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, and Weizhu Chen · 2021
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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
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Blended latent diffusion
Omri Avrahami, Ohad Fried, and Dani Lischinski · 2022
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Blended diffusion for text-driven editing of natural images
Omri Avrahami, Dani Lischinski, and Ohad Fried · 2022
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An image is worth one word: Personalizing text-to-image generation using textual inversion, 2022
Rinon Gal, Yuval Alaluf, Yuval Atzmon, Or Patashnik, Amit H. Bermano, Gal Chechik, and Daniel Cohen-Or · 2022
Earlier work this paper cites.
Prompt-to-prompt image editing with cross attention control
Amir Hertz, Ron Mokady, Jay Tenenbaum, Kfir Aberman, Yael Pritch, and Daniel Cohen-Or · 2022
Earlier work this paper cites.
Classifier-free diffusion guidance
Jonathan Ho · 2022
Cited alongside, same era.
Hierarchical text-conditional image generation with clip latents
Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, and Mark Chen · 2022
Cited alongside, same era.
High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
Cited alongside, same era.
Photorealistic text-to-image diffusion models with deep language understanding
Chitwan Saharia, William Chan, Saurabh Saxena, Lala Li, Jay Whang, Emily L Denton, Kamyar Ghasemipour, Raphael Gontijo Lopes, Burcu Karagol Ayan, Tim Salimans, Jonathan Ho, David J Fleet, and Mohammad Norouzi · 2022
Cited alongside, same era.
Break-a-scene: Extracting multiple concepts from a single image
Omri Avrahami, Kfir Aberman, Ohad Fried, Daniel Cohen-Or, and Dani Lischinski · 2023
Localizing object-level shape variations with text-to-image diffusion models
Or Patashnik, Daniel Garibi, Idan Azuri, Hadar Averbuch-Elor, and Daniel Cohen-Or · 2023
Later among the works it cites.
Sdxl: Improving latent diffusion models for high-resolution image synthesis
Dustin Podell, Zion English, Kyle Lacey, A. Blattmann, Tim Dockhorn, Jonas Muller, Joe Penna, and Robin Rombach · 2023
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Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation
Nataniel Ruiz, Yuanzhen Li, Varun Jampani, Yael Pritch, Michael Rubinstein, and Kfir Aberman · 2023
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Ziplora: Any subject in any style by effectively merging loras
Viraj Shah, Nataniel Ruiz, Forrester Cole, Erika Lu, Svetlana Lazebnik, Yuanzhen Li, and Varun Jampani · 2023
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Cited alongside, same era.
Masactrl: Tuning-free mutual self-attention control for consistent image synthesis and editing
Mingdeng Cao, Xintao Wang, Zhongang Qi, Ying Shan, Xiaohu Qie, and Yinqiang Zheng · 2023
Cited alongside, same era.
Disenbooth: Identity-preserving disentangled tuning for subject-driven text-to-image generation
Hong Chen, Yipeng Zhang, Simin Wu, Xin Wang, Xuguang Duan, Yuwei Zhou, and Wenwu Zhu · 2023
Cited alongside, same era.
Jiwoo Chung, Sangeek Hyun, and Jae-Pil Heo · 2023
Cited alongside, same era.
Diffusion self-guidance for controllable image generation
Dave Epstein, A. Jabri, Ben Poole, Alexei A. Efros, and Aleksander Holynski · 2023
Cited alongside, same era.
Encoder-based domain tuning for fast personalization of text-to-image models
Rinon Gal, Moab Arar, Yuval Atzmon, Amit H. Bermano, Gal Chechik, and Daniel Cohen-Or · 2023
Cited alongside, same era.
Style aligned image generation via shared attention
Amir Hertz, Andrey Voynov, Shlomi Fruchter, and Daniel Cohen-Or · 2023
Cited alongside, same era.
Taming encoder for zero fine-tuning image customization with text-to-image diffusion models, 2023
Xuhui Jia, Yang Zhao, Kelvin C. K. Chan, Yandong Li, Han Zhang, Boqing Gong, Tingbo Hou, Huisheng Wang, and Yu-Chuan Su · 2023
Cited alongside, same era.
Kihyuk Sohn, Nataniel Ruiz, Kimin Lee, Daniel Castro Chin, Irina Blok, Huiwen Chang, Jarred Barber, Lu Jiang, Glenn Entis, Yuanzhen Li, et al · 2023
Later among the works it cites.
Plug-and-play diffusion features for text-driven image-to-image translation
Narek Tumanyan, Michal Geyer, Shai Bagon, and Tali Dekel · 2023
Later among the works it cites.
P+: Extended textual conditioning in text-to-image generation
Andrey Voynov, Qinghao Chu, Daniel Cohen-Or, and Kfir Aberman · 2023
Later among the works it cites.
Elite: Encoding visual concepts into textual embeddings for customized text-to-image generation
Yuxiang Wei, Yabo Zhang, Zhilong Ji, Jinfeng Bai, Lei Zhang, and Wangmeng Zuo · 2023
Later among the works it cites.
Boxdiff: Text-to-image synthesis with training-free box-constrained diffusion
Jinheng Xie, Yuexiang Li, Yawen Huang, Haozhe Liu, Wentian Zhang, Yefeng Zheng, and Mike Zheng Shou · 2023
Later among the works it cites.
Ip-adapter: Text compatible image prompt adapter for text-to-image diffusion models
Hu Ye, Jun Zhang, Sibo Liu, Xiao Han, and Wei Yang · 2023
Later among the works it cites.
Adding conditional control to text-to-image diffusion models
Lvmin Zhang, Anyi Rao, and Maneesh Agrawala · 2023
Later among the works it cites.
Ssr-encoder: Encoding selective subject representation for subject-driven generation
Yuxuan Zhang, Jiaming Liu, Yiren Song, Rui Wang, Hao Tang, Jinpeng Yu, Huaxia Li, Xu Tang, Yao Hu, Han Pan, and Zhongliang Jing · 2023
Later among the works it cites.
Implicit style-content separation using b-lora, 2024
Yarden Frenkel, Yael Vinker, Ariel Shamir, and Daniel Cohen-Or · 2024
Closest in time.
Identity decoupling for multi-subject personalization of text-to-image models, 2024
Sangwon Jang, Jaehyeong Jo, Kimin Lee, and Sung Ju Hwang · 2024
Closest in time.
Deadiff: An efficient stylization diffusion model with disentangled representations
Tianhao Qi, Shancheng Fang, Yanze Wu, Hongtao Xie, Jiawei Liu, Lang Chen, Qian He, and Yongdong Zhang · 2024
Closest in time.
Instantstyle: Free lunch towards style-preserving in text-to-image generation
Haofan Wang, Qixun Wang, Xu Bai, Zekui Qin, and Anthony Chen · 2024
Closest in time.
Break-for-make: Modular low-rank adaptations for composable content-style customization
Yu Xu, Fan Tang, Juan Cao, Yuxin Zhang, Oliver Deussen, Weiming Dong, Jintao Li, and Tong-Yee Lee · 2024
Closest in time.