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Diffusion models have established new state of the art in a multitude of computer vision tasks, including image restoration.
Generative Modeling by Estimating Gradients of the Data Distribution
Song, Y. and Ermon, S · 1907
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Reverse-time diffusion equation models
Anderson, B. D · 1982
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Improved Techniques for Training Score-Based Generative Models
Song, Y. and Ermon, S · 2006
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Imagenet: A large-scale hierarchical image database
Deng, J., Dong, W., Socher, R., Li, L.-J., Li, K., and Fei-Fei, L · 2009
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A connection between score matching and denoising autoencoders
Vincent, P · 2011
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Deep unsupervised learning using nonequilibrium thermodynamics
Sohl-Dickstein, J., Weiss, E., Maheswaranathan, N., and Ganguli, S · 2015
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Plug-and-play admm for image restoration: Fixed-point convergence and applications
Chan, S. H., Wang, X., and Elgendy, O. A · 2016
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Gans trained by a two time-scale update rule converge to a local nash equilibrium
Heusel, M., Ramsauer, H., Unterthiner, T., Nessler, B., and Hochreiter, S · 2017
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The perception-distortion tradeoff
Blau, Y. and Michaeli, T · 2018
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Progressive Growing of GANs for Improved Quality, Stability, and Variation
Karras, T., Aila, T., Laine, S., and Lehtinen, J · 2018
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The unreasonable effectiveness of deep features as a perceptual metric
Zhang, R., Isola, P., Efros, A. A., Shechtman, E., and Wang, O · 2018
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A style-based generator architecture for generative adversarial networks
Karras, T., Laine, S., and Aila, T · 2019
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Denoising Diffusion Probabilistic Models
Ho, J., Jain, A., and Abbeel, P · 2020
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Diffwave: A versatile diffusion model for audio synthesis
Kong, Z., Ping, W., Huang, J., Zhao, K., and Catanzaro, B · 2020
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Score-based generative modeling through stochastic differential equations
Song, Y., Sohl-Dickstein, J., Kingma, D. P., Kumar, A., Ermon, S., and Poole, B · 2020
Cited alongside, same era.
Heavy-tailed denoising score matching
Deasy, J., Simidjievski, N., and Liò, P · 2021
Cited alongside, same era.
Diffusion Models Beat GANs on Image Synthesis
Dhariwal, P. and Nichol, A · 2021
Cited alongside, same era.
Robust compressed sensing mri with deep generative priors
Jalal, A., Arvinte, M., Daras, G., Price, E., Dimakis, A. G., and Tamir, J · 2021
Cited alongside, same era.
Stochastic solutions for linear inverse problems using the prior implicit in a denoiser
Kadkhodaie, Z. and Simoncelli, E · 2021
Cited alongside, same era.
Hoogeboom, E. and Salimans, T · 2022
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Progressive deblurring of diffusion models for coarse-to-fine image synthesis
Lee, S., Chung, H., Kim, J., and Ye, J. C · 2022
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Hierarchical text-conditional image generation with clip latents
Ramesh, A., Dhariwal, P., Nichol, A., Chu, C., and Chen, M · 2022
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Generative modelling with inverse heat dissipation
Rissanen, S., Heinonen, M., and Solin, A · 2022
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High-resolution image synthesis with latent diffusion models
Rombach, R., Blattmann, A., Lorenz, D., Esser, P., and Ommer, B · 2022
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Snips: Solving noisy inverse problems stochastically
Kawar, B., Vaksman, G., and Elad, M · 2021
Cited alongside, same era.
SwinIR: Image restoration using Swin Transformer
Liang, J., Cao, J., Sun, G., Zhang, K., Van Gool, L., and Timofte, R · 2021
Cited alongside, same era.
Denoising diffusion gamma models
Nachmani, E., Roman, R. S., and Wolf, L · 2021
Cited alongside, same era.
Image Super-Resolution via Iterative Refinement
Saharia, C., Ho, J., Chan, W., Salimans, T., Fleet, D. J., and Norouzi, M · 2021
Cited alongside, same era.
Cold diffusion: Inverting arbitrary image transforms without noise
Bansal, A., Borgnia, E., Chu, H.-M., Li, J. S., Kazemi, H., Huang, F., Goldblum, M., Geiping, J., and Goldstein, T · 2022
Cited alongside, same era.
Score-based diffusion models for accelerated mri
Chung, H. and Ye, J. C · 2022
Cited alongside, same era.
Soft diffusion: Score matching for general corruptions
Daras, G., Delbracio, M., Talebi, H., Dimakis, A. G., and Milanfar, P · 2022
Cited alongside, same era.
Later among the works it cites.
Photorealistic text-to-image diffusion models with deep language understanding
Saharia, C., Chan, W., Saxena, S., Li, L., Whang, J., Denton, E., Ghasemipour, S. K. S., Ayan, B. K., Mahdavi, S. S., Lopes, R. G., et al · 2022
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Driftrec: Adapting diffusion models to blind image restoration tasks
Welker, S., Chapman, H. N., and Gerkmann, T · 2022
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Deblurring via stochastic refinement
Whang, J., Delbracio, M., Talebi, H., Saharia, C., Dimakis, A. G., and Milanfar, P · 2022
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Inversion by direct iteration: An alternative to denoising diffusion for image restoration
Delbracio, M. and Milanfar, P · 2023
Closest in time.
Iterative α \alpha -(de)blending: a minimalist deterministic diffusion model
Heitz, E., Belcour, L., and Chambon, T · 2023
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I 2 I SB: Image-to-image schrodinger bridge
Liu, G.-H., Vahdat, A., Huang, D.-A., Theodorou, E. A., Nie, W., and Anandkumar, A · 2023
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Star-shaped denoising diffusion probabilistic models
Okhotin, A., Molchanov, D., Arkhipkin, V., Bartosh, G., Alanov, A., and Vetrov, D · 2023
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Resshift: Efficient diffusion model for image super-resolution by residual shifting
Yue, Z., Wang, J., and Loy, C. C · 2024
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