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Diffusion-based models have gained significant popularity for text-to-image generation due to their exceptional image-generation capabilities.
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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Deep unsupervised learning using nonequilibrium thermodynamics
Jascha Sohl-Dickstein, Eric Weiss, Niru Maheswaranathan, and Surya Ganguli · 2015
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Gender bias in coreference resolution: Evaluation and debiasing methods
Jieyu Zhao, Tianlu Wang, Mark Yatskar, Vicente Ordonez, and Kai-Wei Chang · 2018
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Scalable detection of offensive and non-compliant content/logo in product images
Shreyansh Gandhi, Samrat Kokkula, Abon Chaudhuri, Alessandro Magnani, Theban Stanley, Behzad Ahmadi, Venkatesh Kandaswamy, Omer Ovenc, and Shie Mannor · 2020
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Large image datasets: A pyrrhic win for computer vision?
Vinay Uday Prabhu and Abeba Birhane · 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 · 2020
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Classifier-free diffusion guidance
Jonathan Ho and Tim Salimans · 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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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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Elucidating the design space of diffusion-based generative models
Tero Karras, Miika Aittala, Timo Aila, and Samuli Laine · 2022
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Diffusionclip: Text-guided diffusion models for robust image manipulation
Gwanghyun Kim, Taesung Kwon, and Jong Chul Ye · 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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Diffusion autoencoders: Toward a meaningful and decodable representation
Konpat Preechakul, Nattanat Chatthee, Suttisak Wizadwongsa, and Supasorn Suwajanakorn · 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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Red-teaming the stable diffusion safety filter
Javier Rando, Daniel Paleka, David Lindner, Lennart Heim, and Florian Tramèr · 2022
Cited alongside, same era.
High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
Cited alongside, same era.
Can machines help us answering question 16 in datasheets, and in turn reflecting on inappropriate content?
Patrick Schramowski, Christopher Tauchmann, and Kristian Kersting · 2022
Cited alongside, same era.
Unsupervised representation learning from pre-trained diffusion probabilistic models
Zijian Zhang, Zhou Zhao, and Zhijie Lin · 2022
Cited alongside, same era.
Manuel Brack, Felix Friedrich, Patrick Schramowski, and Kristian Kersting · 2023
Cones: Concept neurons in diffusion models for customized generation
Zhiheng Liu, Ruili Feng, Kai Zhu, Yifei Zhang, Kecheng Zheng, Yu Liu, Deli Zhao, Jingren Zhou, and Yang Cao · 2023
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An image is worth 1000 lies: Transferability of adversarial images across prompts on vision-language models
Haochen Luo, Jindong Gu, Fengyuan Liu, and Philip Torr · 2023
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Improving adversarial transferability via model alignment
Avery Ma, Amir-massoud Farahmand, Yangchen Pan, Philip Torr, and Jindong Gu · 2023
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Null-text inversion for editing real images using guided diffusion models
Ron Mokady, Amir Hertz, Kfir Aberman, Yael Pritch, and Daniel Cohen-Or · 2023
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Editing implicit assumptions in text-to-image diffusion models
Hadas Orgad, Bahjat Kawar, and Yonatan Belinkov · 2023
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Cited alongside, same era.
Debiasing vision-language models via biased prompts
Ching-Yao Chuang, Varun Jampani, Yuanzhen Li, Antonio Torralba, and Stefanie Jegelka · 2023
Cited alongside, same era.
Fair diffusion: Instructing text-to-image generation models on fairness
Felix Friedrich, Manuel Brack, Lukas Struppek, Dominik Hintersdorf, Patrick Schramowski, Sasha Luccioni, and Kristian Kersting · 2023
Cited alongside, same era.
Erasing concepts from diffusion models
Rohit Gandikota, Joanna Materzyńska, Jaden Fiotto-Kaufman, and David Bau · 2023
Cited alongside, same era.
Discovering interpretable directions in the semantic latent space of diffusion models
René Haas, Inbar Huberman-Spiegelglas, Rotem Mulayoff, and Tomer Michaeli · 2023
Cited alongside, same era.
Selective amnesia: A continual learning approach to forgetting in deep generative models
Alvin Heng and Harold Soh · 2023
Cited alongside, same era.
Training-free style transfer emerges from h-space in diffusion models
Jaeseok Jeong, Mingi Kwon, and Youngjung Uh · 2023
Cited alongside, same era.
Ablating concepts in text-to-image diffusion models
Nupur Kumari, Bingliang Zhang, Sheng-Yu Wang, Eli Shechtman, Richard Zhang, and Jun-Yan Zhu · 2023
Cited alongside, same era.
Understanding the latent space of diffusion models through the lens of riemannian geometry
Yong-Hyun Park, Mingi Kwon, Jaewoong Choi, Junghyo Jo, and Youngjung Uh · 2023
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Scalable diffusion models with transformers
William Peebles and Saining Xie · 2023
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Safe latent diffusion: Mitigating inappropriate degeneration in diffusion models
Patrick Schramowski, Manuel Brack, Björn Deiseroth, and Kristian Kersting · 2023
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Freeu: Free lunch in diffusion u-net
Chenyang Si, Ziqi Huang, Yuming Jiang, and Ziwei Liu · 2023
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Linear spaces of meanings: Compositional structures in vision-language models
Matthew Trager, Pramuditha Perera, Luca Zancato, Alessandro Achille, Parminder Bhatia, and Stefano Soatto · 2023
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Plug-and-play diffusion features for text-driven image-to-image translation
Narek Tumanyan, Michal Geyer, Shai Bagon, and Tali Dekel · 2023
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Infodiffusion: Representation learning using information maximizing diffusion models
Yingheng Wang, Yair Schiff, Aaron Gokaslan, Weishen Pan, Fei Wang, Christopher De Sa, and Volodymyr Kuleshov · 2023
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Uncovering the disentanglement capability in text-to-image diffusion models
Qiucheng Wu, Yujian Liu, Handong Zhao, Ajinkya Kale, Trung Bui, Tong Yu, Zhe Lin, Yang Zhang, and Shiyu Chang · 2023
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Unified concept editing in diffusion models
Rohit Gandikota, Hadas Orgad, Yonatan Belinkov, Joanna Materzyńska, and David Bau · 2024
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