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Text-to-image diffusion models have achieved remarkable success in generating high-quality contents from text prompts.
Affective discrimination of stimuli that cannot be recognized
William Raft Kunst-Wilson and R. B Zajonc · 1980
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Mere exposure: A gateway to the subliminal
Robert B Zajonc · 2001
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U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
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The unreasonable effectiveness of deep features as a perceptual metric
Richard Zhang, Phillip Isola, Alexei A. Efros, Eli Shechtman, and Oliver Wang · 2018
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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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, Gretchen Krueger, and Ilya Sutskever · 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
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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 · 2021
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Huggingface
Hugging Face · 2022
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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 · 2022
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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 · 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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Blended latent diffusion
Omri Avrahami, Ohad Fried, and Dani Lischinski · 2023
Cited alongside, same era.
Trojdiff: Trojan attacks on diffusion models with diverse targets
Weixin Chen, Dawn Song, and Bo Li · 2023
Cited alongside, same era.
How to backdoor diffusion models?
Sheng-Yen Chou, Pin-Yu Chen, and Tsung-Yi Ho · 2023
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 Haim Bermano, Gal Chechik, and Daniel Cohen-Or · 2023
Cited alongside, same era.
Dreamedit: Subject-driven image editing
Tianle Li, Max Ku, Cong Wei, and Wenhu Chen · 2023
Cited alongside, same era.
Scaling open-vocabulary object detection
Matthias Minderer, Alexey A. Gritsenko, and Neil Houlsby · 2023
Cited alongside, same era.
Personalization as a shortcut for few-shot backdoor attack against text-to-image diffusion models
Yihao Huang, Felix Juefei-Xu, Qing Guo, Jie Zhang, Yutong Wu, Ming Hu, Tianlin Li, Geguang Pu, and Yang Liu · 2024
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Disguised copyright infringement of latent diffusion models
Yiwei Lu, Matthew Y. R. Yang, Zuoqiu Liu, Gautam Kamath, and Yaoliang Yu · 2024
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Tarot card of raider waite 1920 dataset
Multimodalart · 2024
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Injecting bias in text-to-image models via composite-trigger backdoors
Ali Naseh, Jaechul Roh, Eugene Bagdasaryan, and Amir Houmansadr · 2024
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Hello gpt-4o
OpenAI · 2024
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Dinov2: Learning robust visual features without supervision
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Scalable diffusion models with transformers
William Peebles and Saining Xie · 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.
Rickrolling the artist: Injecting backdoors into text encoders for text-to-image synthesis
Lukas Struppek, Dominik Hintersdorf, and Kristian Kersting · 2023
Cited alongside, same era.
Text-to-image diffusion models can be easily backdoored through multimodal data poisoning
Shengfang Zhai, Yinpeng Dong, Qingni Shen, Shi Pu, Yuejian Fang, and Hang Su · 2023
Cited alongside, same era.
Elijah: Eliminating backdoors injected in diffusion models via distribution shift
Shengwei An, Sheng-Yen Chou, Kaiyuan Zhang, Qiuling Xu, Guanhong Tao, Guangyu Shen, Siyuan Cheng, Shiqing Ma, Pin-Yu Chen, Tsung-Yi Ho, and Xiangyu Zhang · 2024
Cited alongside, same era.
Midjourney-v6 dataset
Cortex Foundation · 2024
Cited alongside, same era.
Maxime Oquab, Timothée Darcet, Théo Moutakanni, Huy Vo, Marc Szafraniec, Vasil Khalidov, Pierre Fernandez, Daniel Haziza, Francisco Massa, Alaaeldin El-Nouby, Mahmoud Assran, Nicolas Ballas, Wojciech Galuba, Russell Howes, Po-Yao Huang, Shang-Wen Li, Ishan Misra, Michael G. Rabbat, Vasu Sharma, Gabriel Synnaeve, Hu Xu, Hervé Jégou, Julien Mairal, Patrick Labatut, Armand Joulin, and Piotr Bojanowski · 2024
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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 · 2024
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Nightshade: Prompt-specific poisoning attacks on text-to-image generative models
Shawn Shan, Wenxin Ding, Josephine Passananti, Stanley Wu, Haitao Zheng, and Ben Y. Zhao · 2024
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Bagm: A backdoor attack for manipulating text-to-image generative models
Jordan Vice, Naveed Akhtar, Richard Hartley, and Ajmal Mian · 2024
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Depth anything: Unleashing the power of large-scale unlabeled data
Lihe Yang, Bingyi Kang, Zilong Huang, Xiaogang Xu, Jiashi Feng, and Hengshuang Zhao · 2024
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Logosticker: Inserting logos into diffusion models for customized generation
Mingkang Zhu, Xi Chen, Zhongdao Wang, Hengshuang Zhao, and Jiaya Jia · 2024
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Identity decoupling for multi-subject personalization of text-to-image models
Sangwon Jang, Jaehyeong Jo, Kimin Lee, and Sung Ju Hwang · 2025
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