- See Also
-
Links
- “Generalizing Factorization of GANs by Characterizing Convolutional Layers”, Et Al 2022
- “PPCD-GAN: Progressive Pruning and Class-Aware Distillation for Large-Scale Conditional GANs Compression”, Et Al 2022
- “Polarity Sampling: Quality and Diversity Control of Pre-Trained Generative Networks via Singular Values”, Et Al 2022
- “BigDatasetGAN: Synthesizing ImageNet With Pixel-wise Annotations”, Et Al 2022
- “Scatterbrain: Unifying Sparse and Low-rank Attention Approximation”, Et Al 2021
- “Telling Creative Stories Using Generative Visual Aids”, 2021
- “DP-LaSE: Discovering Density-Preserving Latent Space Walks in GANs for Semantic Image Transformations”, Et Al 2021
- “CDM: Cascaded Diffusion Models for High Fidelity Image Generation”, Et Al 2021
- “Diffusion Models Beat GANs on Image Synthesis”, 2021
- “MineGAN++: Mining Generative Models for Efficient Knowledge Transfer to Limited Data Domains”, Et Al 2021
- “Generating Images from Caption and vice Versa via CLIP-Guided Generative Latent Space Search”, Et Al 2021
- “Data Instance Prior for Transfer Learning in GANs”, Et Al 2020
- “Network-to-Network Translation With Conditional Invertible Neural Networks”, Et Al 2020
- “SMYRF: Efficient Attention Using Asymmetric Clustering”, Et Al 2020
- “Not-so-BigGAN: Generating High-Fidelity Images on Small Compute With Wavelet-based Super-Resolution”, Et Al 2020
- “Evolving Normalization-Activation Layers”, Et Al 2020
- “GANSpace: Discovering Interpretable GAN Controls”, Et Al 2020
- “A U-Net Based Discriminator for Generative Adversarial Networks”, Et Al 2020
- “Improved Consistency Regularization for GANs”, Et Al 2020
- “MineGAN: Effective Knowledge Transfer from GANs to Target Domains With Few Images”, Et Al 2019
- “Detecting GAN Generated Errors”, Et Al 2019
- “Artbreeder”, 2019
- “BigGAN: Large Scale GAN Training for High Fidelity Natural Image Synthesis § 4.2 Characterizing Instability: The Discriminator”, Et Al 2019 (page 6 Org Deepmind)
- “Large Scale Adversarial Representation Learning”, 2019
- “Improved Precision and Recall Metric for Assessing Generative Models”, Et Al 2019
- “Anime Neural Net Graveyard”, 2019
- “Making Anime With BigGAN”, 2019
- “Discriminator Rejection Sampling”, Et Al 2018
- “BigGAN: Large Scale GAN Training For High Fidelity Natural Image Synthesis § 5.2 Additional Evaluation On JFT-300M”, Et Al 2018 (page 8 Org Deepmind)
- “Large Scale GAN Training for High Fidelity Natural Image Synthesis”, Et Al 2018
- “The Unusual Effectiveness of Averaging in GAN Training”, Et Al 2018
- “Self-Attention Generative Adversarial Networks”, Et Al 2018
- “Spectral Norm Regularization for Improving the Generalizability of Deep Learning”, 2017
- Miscellaneous
- Link Bibliography
See Also
Links
“Generalizing Factorization of GANs by Characterizing Convolutional Layers”, Et Al 2022
“Generalizing Factorization of GANs by Characterizing Convolutional Layers”, 2022-07-18 (; similar; bibliography)
“PPCD-GAN: Progressive Pruning and Class-Aware Distillation for Large-Scale Conditional GANs Compression”, Et Al 2022
“PPCD-GAN: Progressive Pruning and Class-Aware Distillation for Large-Scale Conditional GANs Compression”, 2022-03-16 (; similar)
“Polarity Sampling: Quality and Diversity Control of Pre-Trained Generative Networks via Singular Values”, Et Al 2022
“Polarity Sampling: Quality and Diversity Control of Pre-Trained Generative Networks via Singular Values”, 2022-03-03 (; similar; bibliography)
“BigDatasetGAN: Synthesizing ImageNet With Pixel-wise Annotations”, Et Al 2022
“BigDatasetGAN: Synthesizing ImageNet with Pixel-wise Annotations”, 2022-01-12 (; backlinks; similar; bibliography)
“Scatterbrain: Unifying Sparse and Low-rank Attention Approximation”, Et Al 2021
“Scatterbrain: Unifying Sparse and Low-rank Attention Approximation”, 2021-10-28 (; similar; bibliography)
“Telling Creative Stories Using Generative Visual Aids”, 2021
“Telling Creative Stories Using Generative Visual Aids”, 2021-10-27 (; similar)
“DP-LaSE: Discovering Density-Preserving Latent Space Walks in GANs for Semantic Image Transformations”, Et Al 2021
“DP-LaSE: Discovering Density-Preserving Latent Space Walks in GANs for Semantic Image Transformations”, 2021-08-22 (; similar)
“CDM: Cascaded Diffusion Models for High Fidelity Image Generation”, Et Al 2021
“CDM: Cascaded Diffusion Models for High Fidelity Image Generation”, 2021-06-09 (; similar; bibliography)
“Diffusion Models Beat GANs on Image Synthesis”, 2021
“Diffusion Models Beat GANs on Image Synthesis”, 2021-05-11 (; similar; bibliography)
“MineGAN++: Mining Generative Models for Efficient Knowledge Transfer to Limited Data Domains”, Et Al 2021
“MineGAN++: Mining Generative Models for Efficient Knowledge Transfer to Limited Data Domains”, 2021-04-28 (; similar; bibliography)
“Generating Images from Caption and vice Versa via CLIP-Guided Generative Latent Space Search”, Et Al 2021
“Generating images from caption and vice versa via CLIP-Guided Generative Latent Space Search”, 2021-02-02 (; similar; bibliography)
“Data Instance Prior for Transfer Learning in GANs”, Et Al 2020
“Data Instance Prior for Transfer Learning in GANs”, 2020-12-08 (; similar)
“Network-to-Network Translation With Conditional Invertible Neural Networks”, Et Al 2020
“Network-to-Network Translation with Conditional Invertible Neural Networks”, 2020-10-22 (; similar; bibliography)
“SMYRF: Efficient Attention Using Asymmetric Clustering”, Et Al 2020
“SMYRF: Efficient Attention using Asymmetric Clustering”, 2020-10-11 (; backlinks; similar; bibliography)
“Not-so-BigGAN: Generating High-Fidelity Images on Small Compute With Wavelet-based Super-Resolution”, Et Al 2020
“not-so-BigGAN: Generating High-Fidelity Images on Small Compute with Wavelet-based Super-Resolution”, 2020-09-09 (; backlinks; similar; bibliography)
“Evolving Normalization-Activation Layers”, Et Al 2020
“Evolving Normalization-Activation Layers”, 2020-04-06 (; similar)
“GANSpace: Discovering Interpretable GAN Controls”, Et Al 2020
“GANSpace: Discovering Interpretable GAN Controls”, 2020-04-06 (; backlinks; similar)
“A U-Net Based Discriminator for Generative Adversarial Networks”, Et Al 2020
“A U-Net Based Discriminator for Generative Adversarial Networks”, 2020-02-28 (; backlinks; similar; bibliography)
“Improved Consistency Regularization for GANs”, Et Al 2020
“Improved Consistency Regularization for GANs”, 2020-02-11 (; similar; bibliography)
“MineGAN: Effective Knowledge Transfer from GANs to Target Domains With Few Images”, Et Al 2019
“MineGAN: effective knowledge transfer from GANs to target domains with few images”, 2019-12-11 (; backlinks; similar)
“Detecting GAN Generated Errors”, Et Al 2019
“Detecting GAN generated errors”, 2019-12-02 (; backlinks; similar)
“Artbreeder”, 2019
“Artbreeder”, 2019-09-09 (; backlinks; similar; bibliography)
“BigGAN: Large Scale GAN Training for High Fidelity Natural Image Synthesis § 4.2 Characterizing Instability: The Discriminator”, Et Al 2019 (page 6 Org Deepmind)
“BigGAN: Large Scale GAN Training for High Fidelity Natural Image Synthesis § 4.2 Characterizing Instability: The Discriminator”, 2019-08-26 (similar)
“Large Scale Adversarial Representation Learning”, 2019
“Large Scale Adversarial Representation Learning”, 2019-07-04 (; backlinks; similar)
“Improved Precision and Recall Metric for Assessing Generative Models”, Et Al 2019
“Improved Precision and Recall Metric for Assessing Generative Models”, 2019-04-15 (; backlinks; similar)
“Anime Neural Net Graveyard”, 2019
“Anime Neural Net Graveyard”, 2019-02-04 (; backlinks; similar; bibliography)
“Making Anime With BigGAN”, 2019
“Making Anime With BigGAN”, 2019-02-04 (; backlinks; similar; bibliography)
“Discriminator Rejection Sampling”, Et Al 2018
“Discriminator Rejection Sampling”, 2018-10-16 (; backlinks; similar)
“BigGAN: Large Scale GAN Training For High Fidelity Natural Image Synthesis § 5.2 Additional Evaluation On JFT-300M”, Et Al 2018 (page 8 Org Deepmind)
“BigGAN: Large Scale GAN Training For High Fidelity Natural Image Synthesis § 5.2 Additional Evaluation On JFT-300M”, 2018-09-28 (; similar)
“Large Scale GAN Training for High Fidelity Natural Image Synthesis”, Et Al 2018
“Large Scale GAN Training for High Fidelity Natural Image Synthesis”, 2018-09-28 (; similar)
“The Unusual Effectiveness of Averaging in GAN Training”, Et Al 2018
“The Unusual Effectiveness of Averaging in GAN Training”, 2018-06-12 (; backlinks; similar; bibliography)
“Self-Attention Generative Adversarial Networks”, Et Al 2018
“Self-Attention Generative Adversarial Networks”, 2018-05-21 (; backlinks; similar)
“Spectral Norm Regularization for Improving the Generalizability of Deep Learning”, 2017
“Spectral Norm Regularization for Improving the Generalizability of Deep Learning”, 2017-05-31 (backlinks; similar)
Miscellaneous
Link Bibliography
-
2022-wang.pdf: “Generalizing Factorization of GANs by Characterizing Convolutional Layers”, Yuehui Wang, Qing Wang, Dongyu Zhang: -
https://arxiv.org/abs/2203.01993: “Polarity Sampling: Quality and Diversity Control of Pre-Trained Generative Networks via Singular Values”, Ahmed Imtiaz Humayun, Randall Balestriero, Richard Baraniuk: -
https://arxiv.org/abs/2201.04684: “BigDatasetGAN: Synthesizing ImageNet With Pixel-wise Annotations”, Daiqing Li, Huan Ling, Seung Wook Kim, Karsten Kreis, Adela Barriuso, Sanja Fidler, Antonio Torralba: -
https://arxiv.org/abs/2110.15343#facebook: “Scatterbrain: Unifying Sparse and Low-rank Attention Approximation”, Beidi Chen, Tri Dao, Eric Winsor, Zhao Song, Atri Rudra, Christopher Ré: -
https://cascaded-diffusion.github.io/: “CDM: Cascaded Diffusion Models for High Fidelity Image Generation”, Jonathan Ho, Chitwan Saharia, William Chan, David J. Fleet, Mohammad Norouzi, Tim Salimans: -
https://arxiv.org/abs/2105.05233#openai: “Diffusion Models Beat GANs on Image Synthesis”, Prafulla Dhariwal, Alex Nichol: -
https://arxiv.org/abs/2104.13742: “MineGAN++: Mining Generative Models for Efficient Knowledge Transfer to Limited Data Domains”, Yaxing Wang, Abel Gonzalez-Garcia, Chenshen Wu, Luis Herranz, Fahad Shahbaz Khan, Shangling Jui, Joost van de Weijer: -
https://arxiv.org/abs/2102.01645: “Generating Images from Caption and vice Versa via CLIP-Guided Generative Latent Space Search”, Federico A. Galatolo, Mario G. C. A. Cimino, Gigliola Vaglini: -
https://papers.nips.cc/paper/2020/file/1cfa81af29c6f2d8cacb44921722e753-Paper.pdf: “Network-to-Network Translation With Conditional Invertible Neural Networks”, Robin Rombach, Patrick Esser, Björn Omme: -
https://arxiv.org/abs/2010.05315: “SMYRF: Efficient Attention Using Asymmetric Clustering”, Giannis Daras, Nikita Kitaev, Augustus Odena, Alexandros G. Dimakis: -
https://arxiv.org/abs/2009.04433: “Not-so-BigGAN: Generating High-Fidelity Images on Small Compute With Wavelet-based Super-Resolution”, Seungwook Han, Akash Srivastava, Cole Hurwitz, Prasanna Sattigeri, David D. Cox: -
https://arxiv.org/abs/2002.12655: “A U-Net Based Discriminator for Generative Adversarial Networks”, Edgar Schönfeld, Bernt Schiele, Anna Khoreva: -
https://arxiv.org/abs/2002.04724: “Improved Consistency Regularization for GANs”, Zhengli Zhao, Sameer Singh, Honglak Lee, Zizhao Zhang, Augustus Odena, Han Zhang: -
https://www.artbreeder.com/: “Artbreeder”, Joel Simon: -
face-graveyard: “Anime Neural Net Graveyard”, Gwern Branwen: -
biggan: “Making Anime With BigGAN”, Gwern Branwen: -
https://arxiv.org/abs/1806.04498: “The Unusual Effectiveness of Averaging in GAN Training”, Yasin Yazıcı, Chuan-Sheng Foo, Stefan Winkler, Kim-Hui Yap, Georgios Piliouras, Vijay Chandrasekhar: