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Training-free conditional diffusion models have received great attention in conditional image generation tasks.
Entropy and the central limit theorem
Andrew R. Barron · 1986
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Grad-cam: Visual explanations from deep networks via gradient-based localization
Ramprasaath R. Selvaraju, Michael Cogswell, Abhishek Das, Ramakrishna Vedantam, Devi Parikh, and Dhruv Batra · 2019
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 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 · 2021
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High-resolution image synthesis with latent diffusion models, 2021
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2021
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Diffusion models beat gans on image synthesis
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Denoising diffusion implicit models, 2022
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2022
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Glide: Towards photorealistic image generation and editing with text-guided diffusion models, 2022
Alex Nichol, Prafulla Dhariwal, Aditya Ramesh, Pranav Shyam, Pamela Mishkin, Bob McGrew, Ilya Sutskever, and Mark Chen · 2022
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Sdedit: Guided image synthesis and editing with stochastic differential equations, 2022
Chenlin Meng, Yutong He, Yang Song, Jiaming Song, Jiajun Wu, Jun-Yan Zhu, and Stefano Ermon · 2022
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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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End-to-end diffusion latent optimization improves classifier guidance, 2023
Bram Wallace, Akash Gokul, Stefano Ermon, and Nikhil Naik · 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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Freedom: Training-free energy-guided conditional diffusion model
Jiwen Yu, Yinhuai Wang, Chen Zhao, Bernard Ghanem, and Jian Zhang · 2023
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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
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Diffusion posterior sampling for general noisy inverse problems
Hyungjin Chung, Jeongsol Kim, Michael Thompson Mccann, Marc Louis Klasky, and Jong Chul Ye · 2023
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Pseudoinverse-guided diffusion models for inverse problems
Jiaming Song, Arash Vahdat, Morteza Mardani, and Jan Kautz · 2023
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Adapt and diffuse: Sample-adaptive reconstruction via latent diffusion models, 2023
Zalan Fabian, Berk Tinaz, and Mahdi Soltanolkotabi · 2023
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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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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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Interpretable diffusion via information decomposition, 2023
Xianghao Kong, Ollie Liu, Han Li, Dani Yogatama, and Greg Ver Steeg · 2023
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Morteza Mardani, Jiaming Song, Jan Kautz, and Arash Vahdat · 2023
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Manifold preserving guided diffusion, 2023
Yutong He, Naoki Murata, Chieh-Hsin Lai, Yuhta Takida, Toshimitsu Uesaka, Dongjun Kim, Wei-Hsiang Liao, Yuki Mitsufuji, J. Zico Kolter, Ruslan Salakhutdinov, and Stefano Ermon · 2023
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Monte carlo guided diffusion for bayesian linear inverse problems, 2023
Gabriel Cardoso, Yazid Janati El Idrissi, Sylvain Le Corff, and Eric Moulines · 2023
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Information-theoretic diffusion
Xianghao Kong, Rob Brekelmans, and Greg Ver Steeg · 2023
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A latent space of stochastic diffusion models for zero-shot image editing and guidance
Chen Henry Wu and Fernando De la Torre · 2023
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Jiaming Song, Qinsheng Zhang, Hongxu Yin, Morteza Mardani, Ming-Yu Liu, Jan Kautz, Yongxin Chen, and Arash Vahdat · 2023
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Controlnet++: Improving conditional controls with efficient consistency feedback, 2024
Ming Li, Taojiannan Yang, Huafeng Kuang, Jie Wu, Zhaoning Wang, Xuefeng Xiao, and Chen Chen · 2024
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Training-free content injection using h-space in diffusion models, 2024
Jaeseok Jeong, Mingi Kwon, and Youngjung Uh · 2024
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Freetuner: Any subject in any style with training-free diffusion, 2024
Youcan Xu, Zhen Wang, Jun Xiao, Wei Liu, and Long Chen · 2024
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Guidance with spherical gaussian constraint for conditional diffusion, 2024
Lingxiao Yang, Shutong Ding, Yifan Cai, Jingyi Yu, Jingya Wang, and Ye Shi · 2024
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