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Artistic image stylization aims to render the content provided by text or image with the target style, where content and style decoupling is the key to achieve satisfactory results.
Anglo-Saxon Styles
Catherine E Karkov and George Hardin Brown · 2003
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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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Decoupled weight decay regularization
I Loshchilov · 2017
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Neural discrete representation learning, 2018
Aaron van den Oord, Oriol Vinyals, and Koray Kavukcuoglu · 2018
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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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 Alexander Nichol · 2021
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
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Wikiart - visual art encyclopedia, 2021
Wikipedia · 2021
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Zero-shot text-to-image generation, 2021
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 · 2022
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Hierarchical text-conditional image generation with clip latents
Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, and Mark Chen · 2022
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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, et al · 2022
Cited alongside, same era.
An image is worth one word: Personalizing text-to-image generation using textual inversion
Rinon Gal, Yuval Alaluf, Yuval Atzmon, Or Patashnik, Amit H Bermano, Gal Chechik, and Daniel Cohen-Or · 2022
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Classifier-free diffusion guidance
Jonathan Ho and Tim Salimans · 2022
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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
Cited alongside, same era.
Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models
Csgo: Content-style composition in text-to-image generation
Peng Xing, Haofan Wang, Yanpeng Sun, Qixun Wang, Xu Bai, Hao Ai, Renyuan Huang, and Zechao Li · 2024
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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
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Blip-diffusion: Pre-trained subject representation for controllable text-to-image generation and editing
Dongxu Li, Junnan Li, and Steven Hoi · 2024
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Uni-controlnet: All-in-one control to text-to-image diffusion models
Shihao Zhao, Dongdong Chen, Yen-Chun Chen, Jianmin Bao, Shaozhe Hao, Lu Yuan, and Kwan-Yee K Wong · 2024
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Artbank: Artistic style transfer with pre-trained diffusion model and implicit style prompt bank
Zhanjie Zhang, Quanwei Zhang, Wei Xing, Guangyuan Li, Lei Zhao, Jiakai Sun, Zehua Lan, Junsheng Luan, Yiling Huang, and Huaizhong Lin · 2024
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Junnan Li, Dongxu Li, Silvio Savarese, and Steven Hoi · 2023
Cited alongside, same era.
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
Cited alongside, same era.
Multi-concept customization of text-to-image diffusion
Nupur Kumari, Bingliang Zhang, Richard Zhang, Eli Shechtman, and Jun-Yan Zhu · 2023
Cited alongside, same era.
Styledrop: Text-to-image generation in any style
Kihyuk Sohn, Nataniel Ruiz, Kimin Lee, Daniel Castro Chin, Irina Blok, Huiwen Chang, Jarred Barber, Lu Jiang, Glenn Entis, Yuanzhen Li, et al · 2023
Cited alongside, same era.
Inversion-based style transfer with diffusion models
Yuxin Zhang, Nisha Huang, Fan Tang, Haibin Huang, Chongyang Ma, Weiming Dong, and Changsheng Xu · 2023
Cited alongside, same era.
Composer: Creative and controllable image synthesis with composable conditions
Lianghua Huang, Di Chen, Yu Liu, Yujun Shen, Deli Zhao, and Jingren Zhou · 2023
Cited alongside, same era.
General image-to-image translation with one-shot image guidance
Bin Cheng, Zuhao Liu, Yunbo Peng, and Yue Lin · 2023
Cited alongside, same era.
T2i-adapter: Learning adapters to dig out more controllable ability for text-to-image diffusion models
Chong Mou, Xintao Wang, Liangbin Xie, Yanze Wu, Jian Zhang, Zhongang Qi, and Ying Shan · 2024
Cited alongside, same era.
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Style aligned image generation via shared attention
Amir Hertz, Andrey Voynov, Shlomi Fruchter, and Daniel Cohen-Or · 2024
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Visual style prompting with swapping self-attention
Jaeseok Jeong, Junho Kim, Yunjey Choi, Gayoung Lee, and Youngjung Uh · 2024
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One-shot structure-aware stylized image synthesis
Hansam Cho, Jonghyun Lee, Seunggyu Chang, and Yonghyun Jeong · 2024
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Instantstyle: Free lunch towards style-preserving in text-to-image generation
Haofan Wang, Qixun Wang, Xu Bai, Zekui Qin, and Anthony Chen · 2024
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Artist: Aesthetically controllable text-driven stylization without training
Ruixiang Jiang and Changwen Chen · 2024
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Dreamstyler: Paint by style inversion with text-to-image diffusion models
Namhyuk Ahn, Junsoo Lee, Chunggi Lee, Kunhee Kim, Daesik Kim, Seung-Hun Nam, and Kibeom Hong · 2024
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