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We present SR3, an approach to image Super-Resolution via Repeated Refinement.
Image quality assessment: from error visibility to structural similarity
Zhou Wang, A.C. Bovik, H.R. Sheikh., and E.P. Simoncelli · 2004
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Estimation of non-normalized statistical models by score matching
Aapo Hyvärinen and Peter Dayan · 2005
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Least squares estimation without priors or supervision
Martin Raphan and Eero P Simoncelli · 2011
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A connection between score matching and denoising autoencoders
Pascal Vincent · 2011
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Comparison of four subjective methods for image quality assessment
Rafał K Mantiuk, Anna Tomaszewska, and Radosław Mantiuk · 2012
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Auto-Encoding Variational Bayes
Diederik P Kingma and Max Welling · 2013
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Learning a deep convolutional network for image super-resolution
Chao Dong, Chen Change Loy, Kaiming He, and Xiaoou Tang · 2014
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Generative Adversarial Networks
Ian J Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
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Stochastic backpropagation and approximate inference in deep generative models
Danilo Jimenez Rezende, Shakir Mohamed, and Daan Wierstra · 2014
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Sequence to Sequence Learning with Neural Networks
Ilya Sutskever, Oriol Vinyals, and Quoc Le · 2014
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Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks
Emily Denton, Soumith Chintala, Arthur Szlam, and Rob Fergus · 2015
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Image super-resolution using deep convolutional networks
Chao Dong, Chen Change Loy, Kaiming He, and Xiaoou Tang · 2015
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Unsupervised representation learning with deep convolutional generative adversarial networks
Alec Radford, Luke Metz, and Soumith Chintala · 2015
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Variational inference with normalizing flows
Danilo Rezende and Shakir Mohamed · 2015
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U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
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Imagenet large scale visual recognition challenge
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, et al · 2015
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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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Deep Unsupervised Learning using Nonequilibrium Thermodynamics
Jascha Sohl-Dickstein, Eric A. Weiss, Niru Maheswaranathan, and Surya Ganguli · 2015
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Deep networks for image super-resolution with sparse prior
Zhaowen Wang, Ding Liu, Jianchao Yang, Wei Han, and Thomas Huang · 2015
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Density estimation using real NVP
Laurent Dinh, Jascha Sohl-Dickstein, and Samy Bengio · 2016
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Accelerating the super-resolution convolutional neural network
Chao Dong, Chen Change Loy, and Xiaoou Tang · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Accurate image super-resolution using very deep convolutional networks
Jiwon Kim, Jung Kwon Lee, and Kyoung Mu Lee · 2016
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Deeply-recursive convolutional network for image super-resolution
Jiwon Kim, Jung Kwon Lee, and Kyoung Mu Lee · 2016
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Unrolled generative adversarial networks
Luke Metz, Ben Poole, David Pfau, and Jascha Sohl-Dickstein · 2016
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WaveNet: A Generative Model for Raw Audio
Aäron van den Oord, Sander Dieleman, Heiga Zen, Karen Simonyan, Oriol Vinyals, Alex Graves, Nal Kalchbrenner, Andrew Senior, and Koray Kavukcuoglu · 2016
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Conditional Image Generation with PixelCNN Decoders
Aäron van den Oord, Nal Kalchbrenner, Oriol Vinyals, Lasse Espeholt, Alex Graves, and Koray Kavukcuoglu · 2016
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Glow: Generative Flow with Invertible 1x1 Convolutions
Diederik P. Kingma and Prafulla Dhariwal · 2018
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Image transformer
Niki Parmar, Ashish Vaswani, Jakob Uszkoreit, Lukasz Kaiser, Noam Shazeer, Alexander Ku, and Dustin Tran · 2018
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FiLM: Visual Reasoning with a General Conditioning Layer
Ethan Perez, Florian Strub, Harm De Vries, Vincent Dumoulin, and Aaron Courville · 2018
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Deep Energy Estimator Networks
Saeed Saremi, Arash Mehrjou, Bernhard Schölkopf, and Aapo Hyvärinen · 2018
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Image super-resolution using very deep residual channel attention networks
Yulun Zhang, Kunpeng Li, Kai Li, Lichen Wang, Bineng Zhong, and Yun Fu · 2018
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A Style-Based Generator Architecture for Generative Adversarial Networks
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Psyco: Manifold span reduction for super resolution
Eduardo Pérez-Pellitero, Jordi Salvador, J. Hidalgo, and B. Rosenhahn · 2016
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Pixel recurrent neural networks
Aaron van den Oord, Nal Kalchbrenner, and Koray Kavukcuoglu · 2016
Cited alongside, same era.
Conditional image generation with PixelCNN decoders
Aaron van den Oord, Nal Kalchbrenner, Oriol Vinyals, Lasse Espeholt, Alex Graves, and Koray Kavukcuoglu · 2016
Cited alongside, same era.
Colorful image colorization
Richard Zhang, Phillip Isola, and Alexei A Efros · 2016
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Wasserstein GAN
Martin Arjovsky, Soumith Chintala, and Léon Bottou · 2017
Cited alongside, same era.
Pixel recursive super resolution
Ryan Dahl, Mohammad Norouzi, and Jonathon Shlens · 2017
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Improved training of wasserstein gans
Ishaan Gulrajani, Faruk Ahmed, Martin Arjovsky, Vincent Dumoulin, and Aaron Courville · 2017
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Tero Karras, Samuli Laine, and Timo Aila · 2019
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Generating High Fidelity Images with Subscale Pixel Networks and Multidimensional Upscaling
Jacob Menick and Nal Kalchbrenner · 2019
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Classification accuracy score for conditional generative models
Suman Ravuri and Oriol Vinyals · 2019
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Generating diverse high-fidelity images with vq-vae-2
Ali Razavi, Aaron van den Oord, and Oriol Vinyals · 2019
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Generative Modeling by Estimating Gradients of the Data Distribution
Yang Song and Stefano Ermon · 2019
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Creating high resolution images with a latent adversarial generator
David Berthelot, Peyman Milanfar, and Ian Goodfellow · 2020
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Learning Gradient Fields for Shape Generation
Ruojin Cai, Guandao Yang, Hadar Averbuch-Elor, Zekun Hao, Serge Belongie, Noah Snavely, and Bharath Hariharan · 2020
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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PULSE: Self-supervised photo upsampling via latent space exploration of generative models
Sachit Menon, Alexandru Damian, Shijia Hu, Nikhil Ravi, and Cynthia Rudin · 2020
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Improved Techniques for Training Score-Based Generative Models
Yang Song and Stefano Ermon · 2020
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NVAE: A deep hierarchical variational autoencoder
Arash Vahdat and Jan Kautz · 2020
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HiFaceGAN: Face Renovation via Collaborative Suppression and Replenishment
Lingbo Yang, Chang Liu, Pan Wang, Shanshe Wang, Peiran Ren, Siwei Ma, and Wen Gao · 2020
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Wavelet Flow: Fast Training of High Resolution Normalizing Flows
Jason J. Yu, Konstantinos G. Derpanis, and Marcus A. Brubaker · 2020
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WaveGrad: Estimating Gradients for Waveform Generation
Nanxin Chen, Yu Zhang, Heiga Zen, Ron J. Weiss, Mohammad Norouzi, and William Chan · 2021
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Improved denoising diffusion probabilistic models
Alex Nichol and Prafulla Dhariwal · 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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