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Recent progress in personalized image generation using diffusion models has been significant.
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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The open images dataset v4: Unified image classification, object detection, and visual relationship detection at scale
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Visual genome: Connecting language and vision using crowdsourced dense image annotations
Ranjay Krishna, Yuke Zhu, Oliver Groth, Justin Johnson, Kenji Hata, Joshua Kravitz, Stephanie Chen, Yannis Kalantidis, Li-Jia Li, David A Shamma, et al · 2017
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Coco-stuff: Thing and stuff classes in context. In Proceedings of the IEEE conference on computer vision and pattern recognition . 1209–1218
Holger Caesar, Jasper Uijlings, and Vittorio Ferrari. 2018 · 2018
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Lvis: A dataset for large vocabulary instance segmentation. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition . 5356–5364
Agrim Gupta, Piotr Dollar, and Ross Girshick. 2019 · 2019
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Semantic understanding of scenes through the ade20k dataset
Bolei Zhou, Hang Zhao, Xavier Puig, Tete Xiao, Sanja Fidler, Adela Barriuso, 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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spaCy: Industrial-strength natural language processing in python
Matthew Honnibal, Ines Montani, Sofie Van Landeghem, Adriane Boyd, et al · 2020
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Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon. 2020a · 2020
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Score-based generative modeling through stochastic differential equations
Yang Song, Jascha Sohl-Dickstein, Diederik P Kingma, Abhishek Kumar, Stefano Ermon, and Ben Poole. 2020b · 2020
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Emerging properties in self-supervised vision transformers. In Proceedings of the IEEE/CVF international conference on computer vision . 9650–9660
Mathilde Caron, Hugo Touvron, Ishan Misra, Hervé Jégou, Julien Mairal, Piotr Bojanowski, and Armand Joulin. 2021 · 2021
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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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Learning transferable visual models from natural language supervision. In International conference on machine learning . PMLR, 8748–8763
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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Laion-400m: Open dataset of clip-filtered 400 million image-text pairs
Christoph Schuhmann, Richard Vencu, Romain Beaumont, Robert Kaczmarczyk, Clayton Mullis, Aarush Katta, Theo Coombes, Jenia Jitsev, and Aran Komatsuzaki. 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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Re-imagen: Retrieval-augmented text-to-image generator
Wenhu Chen, Hexiang Hu, Chitwan Saharia, and William W Cohen. 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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GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models. In International Conference on Machine Learning . PMLR, 16784–16804
Alexander Quinn Nichol, Prafulla Dhariwal, Aditya Ramesh, Pranav Shyam, Pamela Mishkin, Bob Mcgrew, Ilya Sutskever, and Mark Chen. 2022 · 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 · 2022
Cited alongside, same era.
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
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, et al · 2022
Cited alongside, same era.
Laion-5b: An open large-scale dataset for training next generation image-text models
Christoph Schuhmann, Romain Beaumont, Richard Vencu, Cade Gordon, Ross Wightman, Mehdi Cherti, Theo Coombes, Aarush Katta, Clayton Mullis, Mitchell Wortsman, et al · 2022
Cited alongside, same era.
Alexander Kirillov, Eric Mintun, Nikhila Ravi, Hanzi Mao, Chloe Rolland, Laura Gustafson, Tete Xiao, Spencer Whitehead, Alexander C Berg, Wan-Yen Lo, et al · 2023
Closest in time.
Dongxu Li, Junnan Li, and Steven CH Hoi. 2023a · 2023
Closest in time.
Grounding dino: Marrying dino with grounded pre-training for open-set object detection
Shilong Liu, Zhaoyang Zeng, Tianhe Ren, Feng Li, Hao Zhang, Jie Yang, Chunyuan Li, Jianwei Yang, Hang Su, Jun Zhu, et al · 2023
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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. 2023b · 2023
Closest in time.
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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
Omri Avrahami, Kfir Aberman, Ohad Fried, Daniel Cohen-Or, and Dani Lischinski. 2023 · 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.
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 · 2023
Cited alongside, same era.
Disenbooth: Identity-preserving disentangled tuning for subject-driven text-to-image generation
Hong Chen, Yipeng Zhang, Xin Wang, Xuguang Duan, Yuwei Zhou, and Wenwu Zhu. 2023b · 2023
Cited alongside, same era.
PhotoVerse: Tuning-Free Image Customization with Text-to-Image Diffusion Models
Li Chen, Mengyi Zhao, Yiheng Liu, Mingxu Ding, Yangyang Song, Shizun Wang, Xu Wang, Hao Yang, Jing Liu, Kang Du, et al · 2023
Cited alongside, same era.
Subject-driven text-to-image generation via apprenticeship learning
Wenhu Chen, Hexiang Hu, Yandong Li, Nataniel Rui, Xuhui Jia, Ming-Wei Chang, and William W Cohen. 2023a · 2023
Cited alongside, same era.
Gradient-Free Textual Inversion
Zhengcong Fei, Mingyuan Fan, and Junshi Huang. 2023 · 2023
Cited alongside, same era.
Jian Ma, Mingjun Zhao, Chen Chen, Ruichen Wang, Di Niu, Haonan Lu, and Xiaodong Lin. 2023b · 2023
Closest in time.
Unified multi-modal latent diffusion for joint subject and text conditional image generation
Yiyang Ma, Huan Yang, Wenjing Wang, Jianlong Fu, and Jiaying Liu. 2023a · 2023
Closest in time.
Royi Rassin, Eran Hirsch, Daniel Glickman, Shauli Ravfogel, Yoav Goldberg, and Gal Chechik. 2023 · 2023
Closest in time.
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
Closest in time.
Instantbooth: Personalized text-to-image generation without test-time finetuning
Jing Shi, Wei Xiong, Zhe Lin, and Hyun Joon Jung. 2023 · 2023
Closest in time.
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 · 2023
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Key-locked rank one editing for text-to-image personalization
Yoad Tewel, Rinon Gal, Gal Chechik, and Yuval Atzmon. 2023 · 2023
Closest in time.
P + P+ : Extended Textual Conditioning in Text-to-Image Generation
Andrey Voynov, Qinghao Chu, Daniel Cohen-Or, and Kfir Aberman. 2023 · 2023
Closest in time.
Compositional text-to-image synthesis with attention map control of diffusion models
Ruichen Wang, Zekang Chen, Chen Chen, Jian Ma, Haonan Lu, and Xiaodong Lin. 2023a · 2023
Closest in time.
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
Closest in time.
Qiucheng Wu, Yujian Liu, Handong Zhao, Trung Bui, Zhe Lin, Yang Zhang, and Shiyu Chang. 2023 · 2023
Closest in time.
FastComposer: Tuning-Free Multi-Subject Image Generation with Localized Attention
Guangxuan Xiao, Tianwei Yin, William T Freeman, Frédo Durand, and Song Han. 2023 · 2023
Closest in time.
Controllable Textual Inversion for Personalized Text-to-Image Generation
Jianan Yang, Haobo Wang, Ruixuan Xiao, Sai Wu, Gang Chen, and Junbo Zhao. 2023 · 2023
Closest in time.
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 · 2023
Closest in time.
Yufan Zhou, Ruiyi Zhang, Tong Sun, and Jinhui Xu. 2023b · 2023
Closest in time.