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While large language models (LLMs) have revolutionized natural language processing with their task-agnostic capabilities, visual generation tasks such as image translation, style transfer, and character customization still rely heavily on supervised, task-specific datasets.
Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al · 2019
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Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J Liu · 2020
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Language models are few-shot learners
Tom B Brown · 2020
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Photo-realistic emoticon generation using multi-modal input
Paritosh Mittal, Kunal Aggarwal, Pragya Paramita Sahu, Vishal Vatsalya, Soumyajit Mitra, Vikrant Singh, Viswanath Veera, and Shankar M Venkatesan · 2020
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Sdedit: Guided image synthesis and editing with stochastic differential equations
Chenlin Meng, Yutong He, Yang Song, Jiaming Song, Jiajun Wu, Jun-Yan Zhu, and Stefano Ermon · 2021
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Training language models to follow instructions with human feedback
Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, et al · 2022
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Opt: Open pre-trained transformer language models
Susan Zhang, Stephen Roller, Naman Goyal, Mikel Artetxe, Moya Chen, Shuohui Chen, Christopher Dewan, Mona Diab, Xian Li, Xi Victoria Lin, et al · 2022
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Giorgio Giannone, Didrik Nielsen, and Ole Winther · 2022
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Glide: Towards photorealistic image generation and editing with text-guided diffusion models, 2022
Alex Nichol, Prafulla Dhariwal, Aditya Ramesh, Pranav Shyam, Pamela Mishkin, Bob McGrew, Ilya Sutskever, and Mark Chen · 2022
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Photorealistic text-to-image diffusion models with deep language understanding, 2022
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, Jonathan Ho, David J Fleet, and Mohammad Norouzi · 2022
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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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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
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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 · 2022
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Prompt-to-prompt image editing with cross attention control
Amir Hertz, Ron Mokady, Jay Tenenbaum, Kfir Aberman, Yael Pritch, and Daniel Cohen-Or · 2022
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Advancing pose-guided image synthesis with progressive conditional diffusion models
Fei Shen, Hu Ye, Jun Zhang, Cong Wang, Xiao Han, and Wei Yang · 2023
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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
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Pixel-aware stable diffusion for realistic image super-resolution and personalized stylization
Tao Yang, Rongyuan Wu, Peiran Ren, Xuansong Xie, and Lei Zhang · 2023
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Continual diffusion: Continual customization of text-to-image diffusion with c-lora
James Seale Smith, Yen-Chang Hsu, Lingyu Zhang, Ting Hua, Zsolt Kira, Yilin Shen, and Hongxia Jin · 2023
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Lcm-lora: A universal stable-diffusion acceleration module
Simian Luo, Yiqin Tan, Suraj Patil, Daniel Gu, Patrick von Platen, Apolinário Passos, Longbo Huang, Jian Li, and Hang Zhao · 2023
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Adding conditional control to text-to-image diffusion models, 2023
Lvmin Zhang, Anyi Rao, and Maneesh Agrawala · 2023
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Generating coherent comic with rich story using chatgpt and stable diffusion
Ze Jin and Zorina Song · 2023
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Sketch-guided text-to-image diffusion models
Andrey Voynov, Kfir Aberman, and Daniel Cohen-Or · 2023
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Diffusing colors: Image colorization with text guided diffusion
Nir Zabari, Aharon Azulay, Alexey Gorkor, Tavi Halperin, and Ohad Fried · 2023
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Diffusart: Enhancing line art colorization with conditional diffusion models
Hernan Carrillo, Michaël Clément, Aurélie Bugeau, and Edgar Simo-Serra · 2023
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Handwritten text generation with character-specific encoding for style imitation
Jan Zdenek and Hideki Nakayama · 2023
Cited alongside, same era.
Character as pixels: A controllable prompt adversarial attacking framework for black-box text guided image generation models
Ziyi Kou, Shichao Pei, Yijun Tian, and Xiangliang Zhang · 2023
Cited alongside, same era.
Zero123++: a single image to consistent multi-view diffusion base model
Ruoxi Shi, Hansheng Chen, Zhuoyang Zhang, Minghua Liu, Chao Xu, Xinyue Wei, Linghao Chen, Chong Zeng, and Hao Su · 2023
Cited alongside, same era.
Scalable diffusion models with transformers
William Peebles and Saining Xie · 2023
Cited alongside, same era.
Customizing text-to-image models with a single image pair
Maxwell Jones, Sheng-Yu Wang, Nupur Kumari, David Bau, and Jun-Yan Zhu · 2024
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Diffstyler: Controllable dual diffusion for text-driven image stylization
Nisha Huang, Yuxin Zhang, Fan Tang, Chongyang Ma, Haibin Huang, Weiming Dong, and Changsheng Xu · 2024
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Fontdiffuser: One-shot font generation via denoising diffusion with multi-scale content aggregation and style contrastive learning
Zhenhua Yang, Dezhi Peng, Yuxin Kong, Yuyi Zhang, Cong Yao, and Lianwen Jin · 2024
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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
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Semantica: An adaptable image-conditioned diffusion model
Manoj Kumar, Neil Houlsby, and Emiel Hoogeboom · 2024
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Smartbrush: Text and shape guided object inpainting with diffusion model
Shaoan Xie, Zhifei Zhang, Zhe Lin, Tobias Hinz, and Kun Zhang · 2023
Cited alongside, same era.
Emu: Enhancing image generation models using photogenic needles in a haystack, 2023
Xiaoliang Dai, Ji Hou, Chih-Yao Ma, Sam Tsai, Jialiang Wang, Rui Wang, Peizhao Zhang, Simon Vandenhende, Xiaofang Wang, Abhimanyu Dubey, Matthew Yu, Abhishek Kadian, Filip Radenovic, Dhruv Mahajan, Kunpeng Li, Yue Zhao, Vladan Petrovic, Mitesh Kumar Singh, Simran Motwani, Yi Wen, Yiwen Song, Roshan Sumbaly, Vignesh Ramanathan, Zijian He, Peter Vajda, and Devi Parikh · 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.
Fastcomposer: Tuning-free multi-subject image generation with localized attention
Guangxuan Xiao, Tianwei Yin, William T. Freeman, Frédo Durand, and Song Han · 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.
Versatile diffusion: Text, images and variations all in one diffusion model
Xingqian Xu, Zhangyang Wang, Gong Zhang, Kai Wang, and Humphrey Shi · 2023
Cited alongside, same era.
Face0: Instantaneously conditioning a text-to-image model on a face
Dani Valevski, Danny Lumen, Yossi Matias, and Yaniv Leviathan · 2023
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Prompt-free diffusion: Taking” text” out of text-to-image diffusion models
Xingqian Xu, Jiayi Guo, Zhangyang Wang, Gao Huang, Irfan Essa, and Humphrey Shi · 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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Control color: Multimodal diffusion-based interactive image colorization
Zhexin Liang, Zhaochen Li, Shangchen Zhou, Chongyi Li, and Chen Change Loy · 2024
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Flux.1, 2024
Black Forest Labs · 2024
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Mint-1t: Scaling open-source multimodal data by 10x: A multimodal dataset with one trillion tokens
Anas Awadalla, Le Xue, Oscar Lo, Manli Shu, Hannah Lee, Etash Kumar Guha, Matt Jordan, Sheng Shen, Mohamed Awadalla, Silvio Savarese, et al · 2024
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Storydiffusion: Consistent self-attention for long-range image and video generation
Yupeng Zhou, Daquan Zhou, Ming-Ming Cheng, Jiashi Feng, and Qibin Hou · 2024
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Processpainter: Learn painting process from sequence data, 2024
Yiren Song, Shijie Huang, Chen Yao, Xiaojun Ye, Hai Ci, Jiaming Liu, Yuxuan Zhang, and Mike Zheng Shou · 2024
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Idadapter: Learning mixed features for tuning-free personalization of text-to-image models, 2024
Siying Cui, Jia Guo, Xiang An, Jiankang Deng, Yongle Zhao, Xinyu Wei, and Ziyong Feng · 2024
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ViPer: Visual personalization of generative models via individual preference learning
Sogand Salehi, Mahdi Shafiei, Teresa Yeo, Roman Bachmann, and Amir Zamir · 2024
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Personalized residuals for concept-driven text-to-image generation
Cusuh Ham, Matthew Fisher, James Hays, Nicholas Kolkin, Yuchen Liu, Richard Zhang, and Tobias Hinz · 2024
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Instantid: Zero-shot identity-preserving generation in seconds
Qixun Wang, Xu Bai, Haofan Wang, Zekui Qin, and Anthony Chen · 2024
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Storyimager: A unified and efficient framework for coherent story visualization and completion
Ming Tao, Bing-Kun Bao, Hao Tang, Yaowei Wang, and Changsheng Xu · 2024
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Dreamidentity: Enhanced editability for efficient face-identity preserved image generation
Zhuowei Chen, Shancheng Fang, Wei Liu, Qian He, Mengqi Huang, and Zhendong Mao · 2024
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Training-free composite scene generation for layout-to-image synthesis, 2024
Jiaqi Liu, Tao Huang, and Chang Xu · 2024
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Gvdiff: Grounded text-to-video generation with diffusion models, 2024
Huanzhang Dou, Ruixiang Li, Wei Su, and Xi Li · 2024
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Universal guidance for diffusion models
Arpit Bansal, Hong-Min Chu, Avi Schwarzschild, Soumyadip Sengupta, Micah Goldblum, Jonas Geiping, and Tom Goldstein · 2024
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Generative multimodal models are in-context learners, 2024
Quan Sun, Yufeng Cui, Xiaosong Zhang, Fan Zhang, Qiying Yu, Zhengxiong Luo, Yueze Wang, Yongming Rao, Jingjing Liu, Tiejun Huang, and Xinlong Wang · 2024
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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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Jedi: Joint-image diffusion models for finetuning-free personalized text-to-image generation
Yu Zeng, Vishal M Patel, Haochen Wang, Xun Huang, Ting-Chun Wang, Ming-Yu Liu, and Yogesh Balaji · 2024
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