Fetching the paper…
Reading the bibliography…
Single image generation (SIG), described as generating diverse samples that have similar visual content with the given single image, is first introduced by SinGAN which builds a pyramid of GANs to progressively learn the internal patch distribution of the single image.
Diversity-Sensitive Conditional Generative Adversarial Networks
Yang, D.; Hong, S.; Jang, Y.; Zhao, T.; and Lee, H. 2019 · 1901
Earlier work this paper cites.
Nonlinear total variation based noise removal algorithms
Rudin, L.; Osher, S.; and Fatemi, E. 1992 · 1992
Earlier work this paper cites.
Exploiting Deep Generative Prior for Versatile Image Restoration and Manipulation
Pan, X.; Zhan, X.; Dai, B.; Lin, D.; Loy, C. C.; and Luo, P. 2020 · 2003
Earlier work this paper cites.
A non-local algorithm for image denoising
Buades, A.; Coll, B.; and Morel, J. 2005 · 2005
Earlier work this paper cites.
Transforming and Projecting Images into Class-conditional Generative Networks
Huh, M.; Zhang, R.; Zhu, J.-Y.; Paris, S.; and Hertzmann, A. 2020 · 2005
Earlier work this paper cites.
Hierarchical Patch VAE-GAN: Generating Diverse Videos from a Single Sample
Gur, S.; Benaim, S.; and Wolf, L. 2020 · 2006
Earlier work this paper cites.
Video collage: presenting a video sequence using a single image
Mei, T.; Yang, B.; Yang, S.; and Hua, X. 2008 · 2008
Earlier work this paper cites.
PatchMatch: a randomized correspondence algorithm for structural image editing
Barnes, C.; Shechtman, E.; Finkelstein, A.; and Goldman, D. B. 2009 · 2009
Earlier work this paper cites.
Imagenet: A large-scale hierarchical image database
Deng, J.; Dong, W.; Socher, R.; Li, L.-J.; Li, K.; and Fei-Fei, L. 2009 · 2009
Earlier work this paper cites.
Positional Encoding as Spatial Inductive Bias in GANs
Xu, R.; Wang, X.; Chen, K.; Zhou, B.; and Loy, C. C. 2020 · 2012
Earlier work this paper cites.
Auto-encoding variational bayes
Kingma, D. P.; and Welling, M. 2013 · 2013
Earlier work this paper cites.
Generative adversarial nets
Goodfellow, I.; Pouget-Abadie, J.; Mirza, M.; Xu, B.; Warde-Farley, D.; Ozair, S.; Courville, A.; and Bengio, Y. 2014 · 2014
Earlier work this paper cites.
Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks
Denton, E. L.; Chintala, S.; Szlam, A. D.; and Fergus, R. 2015 · 2015
Earlier work this paper cites.
Variational Inference with Normalizing Flows
Rezende, D. J.; and Mohamed, S. 2015 · 2015
Earlier work this paper cites.
Very Deep Convolutional Networks for Large-Scale Image Recognition
Simonyan, K.; and Zisserman, A. 2015 · 2015
Earlier work this paper cites.
Lsun: Construction of a large-scale image dataset using deep learning with humans in the loop
Yu, F.; Seff, A.; Zhang, Y.; Song, S.; Funkhouser, T.; and Xiao, J. 2015 · 2015
Earlier work this paper cites.
Texture synthesis with spatial generative adversarial networks
Jetchev, N.; Bergmann, U.; and Vollgraf, R. 2016 · 2016
Cited alongside, same era.
Perceptual losses for real-time style transfer and super-resolution
Johnson, J.; Alahi, A.; and Fei-Fei, L. 2016 · 2016
Cited alongside, same era.
Precomputed Real-Time Texture Synthesis with Markovian Generative Adversarial Networks
Li, C.; and Wand, M. 2016 · 2016
Cited alongside, same era.
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
Radford, A.; Metz, L.; and Chintala, S. 2016 · 2016
Cited alongside, same era.
Pixel Recurrent Neural Networks
van den Oord, A.; Kalchbrenner, N.; and Kavukcuoglu, K. 2016 · 2016
Large Scale GAN Training for High Fidelity Natural Image Synthesis
Brock, A.; Donahue, J.; and Simonyan, K. 2019 · 2019
Later among the works it cites.
“Double-DIP”: Unsupervised Image Decomposition via Coupled Deep-Image-Priors
Gandelsman, Y.; Shocher, A.; and Irani, M. 2019 · 2019
Later among the works it cites.
A style-based generator architecture for generative adversarial networks
Karras, T.; Laine, S.; and Aila, T. 2019 · 2019
Later among the works it cites.
SinGAN: Learning a Generative Model From a Single Natural Image
Shaham, T. R.; Dekel, T.; and Michaeli, T. 2019 · 2019
Later among the works it cites.
InGAN: Capturing and Retargeting the “DNA” of a Natural Image
Shocher, A.; Bagon, S.; Isola, P.; and Irani, M. 2019 · 2019
Later among the works it cites.
Image super-resolution by neural texture transfer
Zhang, Z.; Wang, Z.; Lin, Z.; and Qi, H. 2019 · 2019
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Generative visual manipulation on the natural image manifold
Zhu, J.-Y.; Krähenbühl, P.; Shechtman, E.; and Efros, A. A. 2016 · 2016
Cited alongside, same era.
Wasserstein generative adversarial networks
Arjovsky, M.; Chintala, S.; and Bottou, L. 2017 · 2017
Cited alongside, same era.
Improved training of wasserstein gans
Gulrajani, I.; Ahmed, F.; Arjovsky, M.; Dumoulin, V.; and Courville, A. C. 2017 · 2017
Cited alongside, same era.
Image-to-Image Translation with Conditional Adversarial Networks
Isola, P.; Zhu, J.-Y.; Zhou, T.; and Efros, A. A. 2017 · 2017
Cited alongside, same era.
Progressive growing of gans for improved quality, stability, and variation
Karras, T.; Aila, T.; Laine, S.; and Lehtinen, J. 2017 · 2017
Cited alongside, same era.
Improved texture networks: Maximizing quality and diversity in feed-forward stylization and texture synthesis
Ulyanov, D.; Vedaldi, A.; and Lempitsky, V. 2017 · 2017
Cited alongside, same era.
Which Training Methods for GANs do actually Converge?
Mescheder, L. M.; Geiger, A.; and Nowozin, S. 2018 · 2018
Cited alongside, same era.
Later among the works it cites.
Image processing using multi-code gan prior
Gu, J.; Shen, Y.; and Zhou, B. 2020 · 2020
Later among the works it cites.
Analyzing and Improving the Image Quality of StyleGAN
Karras, T.; Laine, S.; Aittala, M.; Hellsten, J.; Lehtinen, J.; and Aila, T. 2020 · 2020
Later among the works it cites.
MOGAN: Morphologic-structure-aware Generative Learning from a Single Image
Chen, J.; Xu, Q.; Kang, Q.; and Zhou, M. 2021 · 2021
Later among the works it cites.
Drop the GAN: In Defense of Patches Nearest Neighbors as Single Image Generative Models
Granot, N.; Shocher, A.; Feinstein, B.; Bagon, S.; and Irani, M. 2021 · 2021
Later among the works it cites.
Improved techniques for training single-image gans
Hinz, T.; Fisher, M.; Wang, O.; and Wermter, S. 2021 · 2021
Later among the works it cites.
One-Shot GAN: Learning to Generate Samples from Single Images and Videos
Sushko, V.; Gall, J.; and Khoreva, A. 2021 · 2021
Later among the works it cites.
SinIR: Efficient General Image Manipulation with Single Image Reconstruction
Yoo, J.; and Chen, Q. 2021 · 2021
Later among the works it cites.
ExSinGAN: Learning an Explainable Generative Model from a Single Image
Zhang, Z.; Han, C.; and Guo, T. 2021 · 2021
Later among the works it cites.
Patchwise Generative ConvNet: Training Energy-Based Models From a Single Natural Image for Internal Learning
Zheng, Z.; Xie, J.; and Li, P. 2021 · 2021
Later among the works it cites.