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Personalized generation paradigms empower designers to customize visual intellectual properties with the help of textual descriptions by tuning or adapting pre-trained text-to-image models on a few images.
Multi-concept customization of text-to-image diffusion. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition . 1931–1941
Nupur Kumari, Bingliang Zhang, Richard Zhang, Eli Shechtman, and Jun-Yan Zhu. 2023 · 1941
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Visualizing data using t-SNE
Laurens Van der Maaten and Geoffrey Hinton. 2008 · 2008
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Semantic photo manipulation with a generative image prior
David Bau, Hendrik Strobelt, William Peebles, Jonas Wulff, Bolei Zhou, Jun-Yan Zhu, and Antonio Torralba. 2019 · 2019
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel. 2020 · 2020
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AdapterFusion: Non-destructive task composition for transfer learning
Jonas Pfeiffer, Aishwarya Kamath, Andreas Rücklé, Kyunghyun Cho, and Iryna Gurevych. 2020 · 2020
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Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon. 2020 · 2020
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Lora: Low-rank adaptation of large language models
Edward J Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen. 2021 · 2021
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Fedpara: Low-rank hadamard product for communication-efficient federated learning
Nam Hyeon-Woo, Moon Ye-Bin, and Tae-Hyun Oh. 2021 · 2021
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OpenCLIP
Gabriel Ilharco, Mitchell Wortsman, Ross Wightman, Cade Gordon, Nicholas Carlini, Rohan Taori, Achal Dave, Vaishaal Shankar, Hongseok Namkoong, John Miller, Hannaneh Hajishirzi, Ali Farhadi, and Ludwig Schmidt. 2021 · 2021
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ediffi: Text-to-image diffusion models with an ensemble of expert denoisers
Yogesh Balaji, Seungjun Nah, Xun Huang, Arash Vahdat, Jiaming Song, Karsten Kreis, Miika Aittala, Timo Aila, Samuli Laine, Bryan Catanzaro, et al · 2022
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Dreamartist: Towards controllable one-shot text-to-image generation via contrastive prompt-tuning
Ziyi Dong, Pengxu Wei, and Liang Lin. 2022 · 2022
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Krona: Parameter efficient tuning with kronecker adapter
Ali Edalati, Marzieh Tahaei, Ivan Kobyzev, Vahid Partovi Nia, James J Clark, and Mehdi Rezagholizadeh. 2022 · 2022
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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 · 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 · 2022
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Classifier-free diffusion guidance
Jonathan Ho and Tim Salimans. 2022 · 2022
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High-resolution image synthesis with latent diffusion models. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition . 10684–10695
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer. 2022 · 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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Mojtaba Valipour, Mehdi Rezagholizadeh, Ivan Kobyzev, and Ali Ghodsi. 2022 · 2022
Cited alongside, same era.
A Neural Space-Time Representation for Text-to-Image Personalization
Yuval Alaluf, Elad Richardson, Gal Metzer, and Daniel Cohen-Or. 2023 · 2023
Cited alongside, same era.
Break-A-Scene: Extracting Multiple Concepts from a Single Image. In SIGGRAPH Asia 2023 Conference Papers (, Sydney, NSW, Australia,) (SA ’23) . Association for Computing Machinery, New York, NY, USA, Article 96, 12 pages
Omri Avrahami, Kfir Aberman, Ohad Fried, Daniel Cohen-Or, and Dani Lischinski. 2023a · 2023
Cited alongside, same era.
Blended latent diffusion
Omri Avrahami, Ohad Fried, and Dani Lischinski. 2023b · 2023
Cited alongside, same era.
SpaText: Spatio-Textual Representation for Controllable Image Generation. In 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) . 18370–18380
Zero-shot image-to-image translation. In ACM SIGGRAPH 2023 Conference Proceedings . 1–11
Gaurav Parmar, Krishna Kumar Singh, Richard Zhang, Yijun Li, Jingwan Lu, and Jun-Yan Zhu. 2023 · 2023
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unsplash
Martin Philip. 2023 · 2023
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Orthogonal adaptation for modular customization of diffusion models
Ryan Po, Guandao Yang, Kfir Aberman, and Gordon Wetzstein. 2023 · 2023
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Sdxl: Improving latent diffusion models for high-resolution image synthesis
Dustin Podell, Zion English, Kyle Lacey, Andreas Blattmann, Tim Dockhorn, Jonas Müller, Joe Penna, and Robin Rombach. 2023 · 2023
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Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition . 22500–22510
Nataniel Ruiz, Yuanzhen Li, Varun Jampani, Yael Pritch, Michael Rubinstein, and Kfir Aberman. 2023 · 2023
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Omri Avrahami, Thomas Hayes, Oran Gafni, Sonal Gupta, Yaniv Taigman, Devi Parikh, Dani Lischinski, Ohad Fried, and Xi Yin. 2023c · 2023
Cited alongside, same era.
Improving image generation with better captions
James Betker, Gabriel Goh, Li Jing, Tim Brooks, Jianfeng Wang, Linjie Li, Long Ouyang, Juntang Zhuang, Joyce Lee, Yufei Guo, et al · 2023
Cited alongside, same era.
Instructpix2pix: Learning to follow image editing instructions. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition . 18392–18402
Tim Brooks, Aleksander Holynski, and Alexei A Efros. 2023 · 2023
Cited alongside, same era.
Muse: Text-To-Image Generation via Masked Generative Transformers. In Proceedings of the 40th International Conference on Machine Learning (Proceedings of Machine Learning Research, Vol. 202) , Andreas Krause, Emma Brunskill, Kyunghyun Cho, Barbara Engelhardt, Sivan Sabato, and Jonathan Scarlett (Eds.). PMLR, 4055–4075
Huiwen Chang, Han Zhang, Jarred Barber, Aaron Maschinot, Jose Lezama, Lu Jiang, Ming-Hsuan Yang, Kevin Patrick Murphy, William T. Freeman, Michael Rubinstein, Yuanzhen Li, and Dilip Krishnan. 2023 · 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 · 2023
Cited alongside, same era.
Svdiff: Compact parameter space for diffusion fine-tuning
Ligong Han, Yinxiao Li, Han Zhang, Peyman Milanfar, Dimitris Metaxas, and Feng Yang. 2023 · 2023
Cited alongside, same era.
Imagic: Text-based real image editing with diffusion models. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition . 6007–6017
Bahjat Kawar, Shiran Zada, Oran Lang, Omer Tov, Huiwen Chang, Tali Dekel, Inbar Mosseri, and Michal Irani. 2023 · 2023
Cited alongside, same era.
Cones 2: Customizable Image Synthesis with Multiple Subjects
Zhiheng Liu, Yifei Zhang, Yujun Shen, Kecheng Zheng, Kai Zhu, Ruili Feng, Yu Liu, Deli Zhao, Jingren Zhou, and Yang Cao. 2023 · 2023
Cited alongside, same era.
Later among the works it cites.
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 · 2023
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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
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Key-locked rank one editing for text-to-image personalization. In ACM SIGGRAPH 2023 Conference Proceedings . 1–11
Yoad Tewel, Rinon Gal, Gal Chechik, and Yuval Atzmon. 2023 · 2023
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P + P+ : Extended Textual Conditioning in Text-to-Image Generation
Andrey Voynov, Qinghao Chu, Daniel Cohen-Or, and Kfir Aberman. 2023 · 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 · 2023
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Resolving Interference When Merging Models
Prateek Yadav, Derek Tam, Leshem Choshen, Colin Raffel, and Mohit Bansal. 2023 · 2023
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Adaptive budget allocation for parameter-efficient fine-tuning
Qingru Zhang, Minshuo Chen, Alexander Bukharin, Pengcheng He, Yu Cheng, Weizhu Chen, and Tuo Zhao. 2023a · 2023
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ProSpect: Expanded Conditioning for the Personalization of Attribute-aware Image Generation
Yuxin Zhang, Weiming Dong, Fan Tang, Nisha Huang, Haibin Huang, Chongyang Ma, Tong-Yee Lee, Oliver Deussen, and Changsheng Xu. 2023b · 2023
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Subject-driven text-to-image generation via apprenticeship learning
Wenhu Chen, Hexiang Hu, Yandong Li, Nataniel Ruiz, Xuhui Jia, Ming-Wei Chang, and William W Cohen. 2024 · 2024
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Qlora: Efficient finetuning of quantized LLMs
Tim Dettmers, Artidoro Pagnoni, Ari Holtzman, and Luke Zettlemoyer. 2024 · 2024
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CreativeSynth: Creative Blending and Synthesis of Visual Arts based on Multimodal Diffusion
Nisha Huang, Weiming Dong, Yuxin Zhang, Fan Tang, Ronghui Li, Chongyang Ma, Xiu Li, and Changsheng Xu. 2024 · 2024
Closest in time.