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Recent text-to-image customization works have proven successful in generating images of given concepts by fine-tuning diffusion models on a few examples.
Information theory, inference and learning algorithms
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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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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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Conditional generative adversarial nets
Mehdi Mirza and Simon Osindero · 2014
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Energy-based generative adversarial network
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Implicit generation and modeling with energy based models
Yilun Du and Igor Mordatch · 2019
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Autogan: Neural architecture search for generative adversarial networks
Xinyu Gong, Shiyu Chang, Yifan Jiang, and Zhangyang Wang · 2019
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An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, et al · 2020
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Compositional visual generation with energy based models
Yilun Du, Shuang Li, and Igor Mordatch · 2020
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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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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Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2020
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Transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Rémi Louf, Morgan Funtowicz, Joe Davison, Sam Shleifer, Patrick von Platen, Clara Ma, Yacine Jernite, Julien Plu, Canwen Xu, Teven Le Scao, Sylvain Gugger, Mariama Drame, Quentin Lhoest, and Alexander M. Rush · 2020
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Diffusion models beat gans on image synthesis
Prafulla Dhariwal and Alexander Nichol · 2021
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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
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Glide: Towards photorealistic image generation and editing with text-guided diffusion models
Alex Nichol, Prafulla Dhariwal, Aditya Ramesh, Pranav Shyam, Pamela Mishkin, Bob McGrew, Ilya Sutskever, and Mark Chen · 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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ediff-i: Text-to-image diffusion models with an ensemble of expert denoisers
Yogesh Balaji, Seungjun Nah, Xun Huang, Arash Vahdat, Jiaming Song, Qinsheng Zhang, Karsten Kreis, Miika Aittala, Timo Aila, Samuli Laine, et al · 2022
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Re-imagen: Retrieval-augmented text-to-image generator
Wenhu Chen, Hexiang Hu, Chitwan Saharia, and William W Cohen · 2022
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Ziyi Dong, Pengxu Wei, and Liang Lin · 2022
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Training-free structured diffusion guidance for compositional text-to-image synthesis
Weixi Feng, Xuehai He, Tsu-Jui Fu, Varun Jampani, Arjun Akula, Pradyumna Narayana, Sugato Basu, Xin Eric Wang, and William Yang Wang · 2022
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Compositional visual generation with composable diffusion models
Nan Liu, Shuang Li, Yilun Du, Antonio Torralba, and Joshua B Tenenbaum · 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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High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 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
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Diffusers: State-of-the-art diffusion models
Patrick von Platen, Suraj Patil, Anton Lozhkov, Pedro Cuenca, Nathan Lambert, Kashif Rasul, Mishig Davaadorj, Dhruv Nair, Sayak Paul, William Berman, Yiyi Xu, Steven Liu, and Thomas Wolf · 2022
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A neural space-time representation for text-to-image personalization
Yuval Alaluf, Elad Richardson, Gal Metzer, and Daniel Cohen-Or · 2023
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Spatext: Spatio-textual representation for controllable image generation
Omri Avrahami, Thomas Hayes, Oran Gafni, Sonal Gupta, Yaniv Taigman, Devi Parikh, Dani Lischinski, Ohad Fried, and Xi Yin · 2023
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Dreamdiffusion: Generating high-quality images from brain eeg signals
Yunpeng Bai, Xintao Wang, Yan-pei Cao, Yixiao Ge, Chun Yuan, and Ying Shan · 2023
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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 · 2023
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Muse: Text-to-image generation via masked generative transformers
Huiwen Chang, Han Zhang, Jarred Barber, AJ Maschinot, Jose Lezama, Lu Jiang, Ming-Hsuan Yang, Kevin Murphy, William T Freeman, Michael Rubinstein, et al · 2023
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Attend-and-excite: Attention-based semantic guidance for text-to-image diffusion models
Hila Chefer, Yuval Alaluf, Yael Vinker, Lior Wolf, and Daniel Cohen-Or · 2023
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Kai Chen, Enze Xie, Zhe Chen, Lanqing Hong, Zhenguo Li, and Dit-Yan Yeung · 2023
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Seeing beyond the brain: Conditional diffusion model with sparse masked modeling for vision decoding
Zijiao Chen, Jiaxin Qing, Tiange Xiang, Wan Lin Yue, and Juan Helen Zhou · 2023
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Layoutdiffuse: Adapting foundational diffusion models for layout-to-image generation
Jiaxin Cheng, Xiao Liang, Xingjian Shi, Tong He, Tianjun Xiao, and Mu Li · 2023
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Brainvis: Exploring the bridge between brain and visual signals via image reconstruction
Honghao Fu, Zhiqi Shen, Jing Jih Chin, and Hao Wang · 2023
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An image is worth one word: Personalizing text-to-image generation using textual inversion
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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Xiaoshi Wu, Yiming Hao, Keqiang Sun, Yixiong Chen, Feng Zhu, Rui Zhao, and Hongsheng Li · 2023
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A closer look at parameter-efficient tuning in diffusion models
Chendong Xiang, Fan Bao, Chongxuan Li, Hang Su, and Jun Zhu · 2023
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Imagereward: Learning and evaluating human preferences for text-to-image generation, 2023
Jiazheng Xu, Xiao Liu, Yuchen Wu, Yuxuan Tong, Qinkai Li, Ming Ding, Jie Tang, and Yuxiao Dong · 2023
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Magicanimate: Temporally consistent human image animation using diffusion model
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Rinon Gal, Yuval Alaluf, Yuval Atzmon, Or Patashnik, Amit Haim Bermano, Gal Chechik, and Daniel Cohen-or · 2023
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Designing an encoder for fast personalization of text-to-image models
Rinon Gal, Moab Arar, Yuval Atzmon, Amit H Bermano, Gal Chechik, and Daniel Cohen-Or · 2023
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Expressive text-to-image generation with rich text
Songwei Ge, Taesung Park, Jun-Yan Zhu, and Jia-Bin Huang · 2023
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Sparsectrl: Adding sparse controls to text-to-video diffusion models
Yuwei Guo, Ceyuan Yang, Anyi Rao, Maneesh Agrawala, Dahua Lin, and Bo Dai · 2023
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Modulating pretrained diffusion models for multimodal image synthesis
Cusuh Ham, James Hays, Jingwan Lu, Krishna Kumar Singh, Zhifei Zhang, and Tobias Hinz · 2023
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Svdiff: Compact parameter space for diffusion fine-tuning
Ligong Han, Yinxiao Li, Han Zhang, Peyman Milanfar, Dimitris Metaxas, and Feng Yang · 2023
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Dreamtuner: Single image is enough for subject-driven generation
Miao Hua, Jiawei Liu, Fei Ding, Wei Liu, Jie Wu, and Qian He · 2023
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Humansd: A native skeleton-guided diffusion model for human image generation
Xuan Ju, Ailing Zeng, Chenchen Zhao, Jianan Wang, Lei Zhang, and Qiang Xu · 2023
Cited alongside, same era.
Zhongcong Xu, Jianfeng Zhang, Jun Hao Liew, Hanshu Yan, Jia-Wei Liu, Chenxu Zhang, Jiashi Feng, and Mike Zheng Shou · 2023
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Freestyle layout-to-image synthesis
Han Xue, Zhiwu Huang, Qianru Sun, Li Song, and Wenjun Zhang · 2023
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Align, adapt and inject: Sound-guided unified image generation
Yue Yang, Kaipeng Zhang, Yuying Ge, Wenqi Shao, Zeyue Xue, Yu Qiao, and Ping Luo · 2023
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Cle diffusion: Controllable light enhancement diffusion model
Yuyang Yin, Dejia Xu, Chuangchuang Tan, Ping Liu, Yao Zhao, and Yunchao Wei · 2023
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4dgen: Grounded 4d content generation with spatial-temporal consistency
Yuyang Yin, Dejia Xu, Zhangyang Wang, Yao Zhao, and Yunchao Wei · 2023
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Freedom: Training-free energy-guided conditional diffusion model
Jiwen Yu, Yinhuai Wang, Chen Zhao, Bernard Ghanem, and Jian Zhang · 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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I2vgen-xl: High-quality image-to-video synthesis via cascaded diffusion models
Shiwei Zhang, Jiayu Wang, Yingya Zhang, Kang Zhao, Hangjie Yuan, Zhiwu Qin, Xiang Wang, Deli Zhao, and Jingren Zhou · 2023
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Controlvideo: Training-free controllable text-to-video generation
Yabo Zhang, Yuxiang Wei, Dongsheng Jiang, Xiaopeng Zhang, Wangmeng Zuo, and Qi Tian · 2023
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Prospect: Prompt spectrum for attribute-aware personalization of diffusion models
Yuxin Zhang, Weiming Dong, Fan Tang, Nisha Huang, Haibin Huang, Chongyang Ma, Tong-Yee Lee, Oliver Deussen, and Changsheng Xu · 2023
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Tiam – a metric for evaluating alignment in text-to-image generation, 2024
Paul Grimal, Hervé Le Borgne, Olivier Ferret, and Julien Tourille · 2024
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Animatediff: Animate your personalized text-to-image diffusion models without specific tuning
Yuwei Guo, Ceyuan Yang, Anyi Rao, Zhengyang Liang, Yaohui Wang, Yu Qiao, Maneesh Agrawala, Dahua Lin, and Bo Dai · 2024
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Automated black-box prompt engineering for personalized text-to-image generation
Yutong He, Alexander Robey, Naoki Murata, Yiding Jiang, Joshua Williams, George J Pappas, Hamed Hassani, Yuki Mitsufuji, Ruslan Salakhutdinov, and J Zico Kolter · 2024
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Instruct-imagen: Image generation with multi-modal instruction, 2024
Hexiang Hu, Kelvin C. K. Chan, Yu-Chuan Su, Wenhu Chen, Yandong Li, Kihyuk Sohn, Yang Zhao, Xue Ben, Boqing Gong, William Cohen, Ming-Wei Chang, and Xuhui Jia · 2024
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Identity decoupling for multi-subject personalization of text-to-image models, 2024
Sangwon Jang, Jaehyeong Jo, Kimin Lee, and Sung Ju Hwang · 2024
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Concept weaver: Enabling multi-concept fusion in text-to-image models, 2024
Gihyun Kwon, Simon Jenni, Dingzeyu Li, Joon-Young Lee, Jong Chul Ye, and Fabian Caba Heilbron · 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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Unimo-g: Unified image generation through multimodal conditional diffusion, 2024
Wei Li, Xue Xu, Jiachen Liu, and Xinyan Xiao · 2024
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Diffusion4d: Fast spatial-temporal consistent 4d generation via video diffusion models
Hanwen Liang, Yuyang Yin, Dejia Xu, Hanxue Liang, Zhangyang Wang, Konstantinos N Plataniotis, Yao Zhao, and Yunchao Wei · 2024
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Image anything: Towards reasoning-coherent and training-free multi-modal image generation, 2024
Yuanhuiyi Lyu, Xu Zheng, and Lin Wang · 2024
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Cat: Contrastive adapter training for personalized image generation, 2024
Jae Wan Park, Sang Hyun Park, Jun Young Koh, Junha Lee, and Min Song · 2024
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Linguistic binding in diffusion models: Enhancing attribute correspondence through attention map alignment
Royi Rassin, Eran Hirsch, Daniel Glickman, Shauli Ravfogel, Yoav Goldberg, and Gal Chechik · 2024
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Moma: Multimodal llm adapter for fast personalized image generation, 2024
Kunpeng Song, Yizhe Zhu, Bingchen Liu, Qing Yan, Ahmed Elgammal, and Xiao Yang · 2024
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Visual autoregressive modeling: Scalable image generation via next-scale prediction
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Is this loss informative? faster text-to-image customization by tracking objective dynamics
Anton Voronov, Mikhail Khoroshikh, Artem Babenko, and Max Ryabinin · 2024
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U-vap: User-specified visual appearance personalization via decoupled self augmentation
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4dgen: Grounded 4d content generation with spatial-temporal consistency, 2024
Yuyang Yin, Dejia Xu, Zhangyang Wang, Yao Zhao, and Yunchao Wei · 2024
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Dreamlcm: Towards high quality text-to-3d generation via latent consistency model
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Diffusion for natural image matting
Yihan Hu, Yiheng Lin, Wei Wang, Yao Zhao, Yunchao Wei, and Humphrey Shi · 2025
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