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Guidance is a crucial technique for extracting the best performance out of image-generating diffusion models.
Estimation of non-normalized statistical models by score matching
A. Hyvärinen · 2005
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ImageNet: A large-scale hierarchical image database
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A connection between score matching and denoising autoencoders
P. Vincent · 2011
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Deep unsupervised learning using nonequilibrium thermodynamics
J. Sohl-Dickstein, E. Weiss, N. Maheswaranathan, and S. Ganguli · 2015
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GANs trained by a two time-scale update rule converge to a local Nash equilibrium
M. Heusel, H. Ramsauer, T. Unterthiner, B. Nessler, and S. Hochreiter · 2017
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Improved precision and recall metric for assessing generative models
T. Kynkäänniemi, T. Karras, S. Laine, J. Lehtinen, and T. Aila · 2019
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Generative modeling by estimating gradients of the data distribution
Y. Song and S. Ermon · 2019
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Denoising diffusion probabilistic models
J. Ho, A. Jain, and P. Abbeel · 2020
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Classifier-free diffusion guidance
J. Ho and T. Salimans · 2021
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DiffWave: A versatile diffusion model for audio synthesis
Z. Kong, W. Ping, J. Huang, K. Zhao, and B. Catanzaro · 2021
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Improved denoising diffusion probabilistic models
A. Nichol and P. Dhariwal · 2021
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Grad-TTS: A diffusion probabilistic model for text-to-speech
V. Popov, I. Vovk, V. Gogoryan, T. Sadekova, and M. Kudinov · 2021
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Denoising diffusion implicit models
J. Song, C. Meng, and S. Ermon · 2021
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Score-based generative modeling through stochastic differential equations
Y. Song, J. Sohl-Dickstein, D. P. Kingma, A. Kumar, S. Ermon, and B. Poole · 2021
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Guidance: A cheat code for diffusion models
S. Dieleman · 2022
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Imagen Video: High definition video generation with diffusion models
J. Ho, W. Chan, C. Saharia, J. Whang, R. Gao, A. Gritsenko, D. P. Kingma, B. Poole, M. Norouzi, D. J. Fleet, and T. Salimans · 2022
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Video diffusion models
J. Ho, T. Salimans, A. A. Gritsenko, W. Chan, M. Norouzi, and D. J. Fleet · 2022
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Elucidating the design space of diffusion-based generative models
T. Karras, M. Aittala, T. Aila, and S. Laine · 2022
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High-resolution image synthesis with latent diffusion models
R. Rombach, A. Blattmann, D. Lorenz, P. Esser, and B. Ommer · 2022
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Improving image generation with better captions
J. Betker, G. Goh, L. Jing, T. Brooks, J. Wang, L. Li, L. Ouyang, J. Zhuang, J. Lee, Y. Guo, W. Manassra, P. Dhariwal, C. Chu, Y. Jiao, and A. Ramesh · 2023
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DreamBooth: Fine tuning text-to-image diffusion models for subject-driven generation
N. Ruiz, Y. Li, V. Jampani, Y. Pritch, M. Rubinstein, and K. Aberman · 2023
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3D neural field generation using triplane diffusion
J. R. Shue, E. R. Chan, R. Po, Z. Ankner, J. Wu, and G. Wetzstein · 2023
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Exposing flaws of generative model evaluation metrics and their unfair treatment of diffusion models
G. Stein, J. C. Cresswell, R. Hosseinzadeh, Y. Sui, B. L. Ross, V. Villecroze, Z. Liu, A. L. Caterini, J. E. T. Taylor, and G. Loaiza-Ganem · 2023
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Adding conditional control to text-to-image diffusion models
L. Zhang, A. Rao, and M. Agrawala · 2023
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Turning off classifier-free guidance at low noise levels
Alex Birch · 2024
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Stable Diffusion dynamic thresholding
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A. Blattmann, R. Rombach, H. Ling, T. Dockhorn, S. W. Kim, S. Fidler, and K. Kreis · 2023
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Adaptive guidance: Training-free acceleration of conditional diffusion models
A. Castillo, J. Kohler, J. C. Pérez, J. P. Pérez, A. Pumarola, B. Ghanem, P. Arbeláez, and A. Thabet · 2023
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Muse: Text-to-image generation via masked generative transformers
H. Chang, H. Zhang, J. Barber, A. Maschinot, J. Lezama, L. Jiang, M.-H. Yang, K. Murphy, W. T. Freeman, M. Rubinstein, Y. Li, and D. Krishnan · 2023
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An image is worth one word: Personalizing text-to-image generation using textual inversion
R. Gal, Y. Alaluf, Y. Atzmon, O. Patashnik, A. H. Bermano, G. Chechik, and D. Cohen-Or · 2023
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Mdtv2: Masked diffusion transformer is a strong image synthesizer
S. Gao, P. Zhou, M.-M. Cheng, and S. Yan · 2023
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Magic3D: High-resolution text-to-3D content creation
C.-H. Lin, J. Gao, L. Tang, T. Takikawa, X. Zeng, X. Huang, K. Kreis, S. Fidler, M.-Y. Liu, and T.-Y. Lin · 2023
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Scalable diffusion models with transformers
W. Peebles and S. Xie · 2023
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Alex Goodwin · 2024
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Stable Diffusion web UI
AUTOMATIC1111 · 2024
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Dynamical regimes of diffusion models
G. Biroli, T. Bonnaire, V. de Bortoli, and M. Mézard · 2024
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Video generation models as world simulators
T. Brooks, B. Peebles, C. Holmes, W. DePue, Y. Guo, L. Jing, D. Schnurr, J. Taylor, T. Luhman, E. Luhman, C. Ng, R. Wang, and A. Ramesh · 2024
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Adjusting guidance weight as a function of time
Jeremy Howard and Rekil Prashanth · 2024
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Analyzing and improving the training dynamics of diffusion models
T. Karras, M. Aittala, J. Lehtinen, J. Hellsten, T. Aila, and S. Laine · 2024
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Prompting hard or hardly prompting: Prompt inversion for text-to-image diffusion models
S. Mahajan, T. Rahman, K. M. Yi, and L. Sigal · 2024
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SDXL: Improving latent diffusion models for high-resolution image synthesis
D. Podell, Z. English, K. Lacey, A. Blattmann, T. Dockhorn, J. Müller, J. Penna, and R. Rombach · 2024
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Cads: Unleashing the diversity of diffusion models through condition-annealed sampling
S. Sadat, J. Buhmann, D. Bradley, O. Hilliges, and R. M. Weber · 2024
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