‘BigGAN’ tag

Gwern Branwen

‘BigGAN’ tag

See Also
Gwern
- “Making Anime With BigGAN”, Gwern 2019
- “Anime Neural Net Graveyard”, Gwern 2019
Links
Miscellaneous
Bibliography

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Gwern

“Making Anime With BigGAN”, Gwern 2019

Making Anime With BigGAN

“Anime Neural Net Graveyard”, Gwern 2019

Anime Neural Net Graveyard

Links

“Optimal Transport-Based Unsupervised Semantic Disentanglement: A Novel Approach for Efficient Image Editing in GANs”, Liu et al 2023d

Optimal transport-based unsupervised semantic disentanglement: A novel approach for efficient image editing in GANs

“Diffusion Models Beat GANs on Image Classification”, Mukhopadhyay et al 2023

Diffusion Models Beat GANs on Image Classification

“Rosetta Neurons: Mining the Common Units in a Model Zoo”, Dravid et al 2023

Rosetta Neurons: Mining the Common Units in a Model Zoo

“Exposing Flaws of Generative Model Evaluation Metrics and Their Unfair Treatment of Diffusion Models”, Stein et al 2023

Exposing flaws of generative model evaluation metrics and their unfair treatment of diffusion models

“Generalizable Synthetic Image Detection via Language-Guided Contrastive Learning”, Wu et al 2023

Generalizable Synthetic Image Detection via Language-guided Contrastive Learning

“KD-DLGAN: Data Limited Image Generation via Knowledge Distillation”, Cui et al 2023

KD-DLGAN: Data Limited Image Generation via Knowledge Distillation

“SAN: Inducing Metrizability of GAN With Discriminative Normalized Linear Layer”, Takida et al 2023

SAN: Inducing Metrizability of GAN with Discriminative Normalized Linear Layer

“Generalizing Factorization of GANs by Characterizing Convolutional Layers”, Wang et al 2022b

Generalizing Factorization of GANs by Characterizing Convolutional Layers

“PPCD-GAN: Progressive Pruning and Class-Aware Distillation for Large-Scale Conditional GANs Compression”, Vo et al 2022

PPCD-GAN: Progressive Pruning and Class-Aware Distillation for Large-Scale Conditional GANs Compression

“Polarity Sampling: Quality and Diversity Control of Pre-Trained Generative Networks via Singular Values”, Humayun et al 2022

Polarity Sampling: Quality and Diversity Control of Pre-Trained Generative Networks via Singular Values

“BigDatasetGAN: Synthesizing ImageNet With Pixel-Wise Annotations”, Li et al 2022

BigDatasetGAN: Synthesizing ImageNet with Pixel-wise Annotations

“Scatterbrain: Unifying Sparse and Low-Rank Attention Approximation”, Chen et al 2021

Scatterbrain: Unifying Sparse and Low-rank Attention Approximation

“Telling Creative Stories Using Generative Visual Aids”, Ali & Parikh 2021

Telling Creative Stories Using Generative Visual Aids

“DP-LaSE: Discovering Density-Preserving Latent Space Walks in GANs for Semantic Image Transformations”, Li et al 2021b

DP-LaSE: Discovering Density-Preserving Latent Space Walks in GANs for Semantic Image Transformations

“CDM: Cascaded Diffusion Models for High Fidelity Image Generation”, Ho et al 2021

CDM: Cascaded Diffusion Models for High Fidelity Image Generation

“Diffusion Models Beat GANs on Image Synthesis”, Dhariwal & Nichol 2021

Diffusion Models Beat GANs on Image Synthesis

“MineGAN++: Mining Generative Models for Efficient Knowledge Transfer to Limited Data Domains”, Wang et al 2021

MineGAN++: Mining Generative Models for Efficient Knowledge Transfer to Limited Data Domains

“Generating Images from Caption and vice Versa via CLIP-Guided Generative Latent Space Search”, Galatolo et al 2021

Generating images from caption and vice versa via CLIP-Guided Generative Latent Space Search

“Data Instance Prior for Transfer Learning in GANs”, Mangla et al 2020

Data Instance Prior for Transfer Learning in GANs

“Network-To-Network Translation With Conditional Invertible Neural Networks”, Rombach et al 2020

Network-to-Network Translation with Conditional Invertible Neural Networks

“SMYRF: Efficient Attention Using Asymmetric Clustering”, Daras et al 2020

SMYRF: Efficient Attention using Asymmetric Clustering

“Not-So-BigGAN: Generating High-Fidelity Images on Small Compute With Wavelet-Based Super-Resolution”, Han et al 2020

not-so-BigGAN: Generating High-Fidelity Images on Small Compute with Wavelet-based Super-Resolution

“GANSpace: Discovering Interpretable GAN Controls”, Härkönen et al 2020

GANSpace: Discovering Interpretable GAN Controls

“Evolving Normalization-Activation Layers”, Liu et al 2020

Evolving Normalization-Activation Layers

“A U-Net Based Discriminator for Generative Adversarial Networks”, Schönfeld et al 2020

A U-Net Based Discriminator for Generative Adversarial Networks

“Improved Consistency Regularization for GANs”, Zhao et al 2020

Improved Consistency Regularization for GANs

“MineGAN: Effective Knowledge Transfer from GANs to Target Domains With Few Images”, Wang et al 2019

MineGAN: effective knowledge transfer from GANs to target domains with few images

“Detecting GAN Generated Errors”, Zhu et al 2019

Detecting GAN generated errors

“BigGAN: Large Scale GAN Training for High Fidelity Natural Image Synthesis § 4.2 Characterizing Instability: The Discriminator”, Brock et al 2019 (page 6 org deepmind)

BigGAN: Large Scale GAN Training for High Fidelity Natural Image Synthesis § 4.2 Characterizing Instability: The Discriminator

“Large Scale Adversarial Representation Learning”, Donahue & Simonyan 2019

Large Scale Adversarial Representation Learning

“Improved Precision and Recall Metric for Assessing Generative Models”, Kynkäänniemi et al 2019

Improved Precision and Recall Metric for Assessing Generative Models

“Discriminator Rejection Sampling”, Azadi et al 2018

Discriminator Rejection Sampling

“Large Scale GAN Training for High Fidelity Natural Image Synthesis”, Brock et al 2018

Large Scale GAN Training for High Fidelity Natural Image Synthesis

“BigGAN: Large Scale GAN Training For High Fidelity Natural Image Synthesis § 5.2 Additional Evaluation On JFT-300M”, Brock 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

“The Unusual Effectiveness of Averaging in GAN Training”, Yazıcı et al 2018

The Unusual Effectiveness of Averaging in GAN Training

“Self-Attention Generative Adversarial Networks”, Zhang et al 2018

Self-Attention Generative Adversarial Networks

“Spectral Norm Regularization for Improving the Generalizability of Deep Learning”, Yoshida & Miyato 2017

Spectral Norm Regularization for Improving the Generalizability of Deep Learning

“Generate Amazing Anime Pictures With BigGAN. Just Have Fun”

Generate Amazing Anime Pictures With BigGAN. Just Have Fun

“BigGAN-PyTorch: The Author’s Officially Unofficial PyTorch BigGAN Implementation”

BigGAN-PyTorch: The author’s officially unofficial PyTorch BigGAN implementation

“Pytorch Implementation of ‘Large Scale GAN Training For High Fidelity Natural Image Synthesis’ (BigGAN)”

Pytorch implementation of ‘Large Scale GAN Training For High Fidelity Natural Image Synthesis’ (BigGAN)

“Simple Tensorflow Implementation of "Large Scale GAN Training for High Fidelity Natural Image Synthesis" (BigGAN)”

Simple Tensorflow implementation of "Large Scale GAN Training for High Fidelity Natural Image Synthesis" (BigGAN)

“Simple Tensorflow Implementation of "Self-Attention Generative Adversarial Networks" (SAGAN)”

Simple Tensorflow implementation of "Self-Attention Generative Adversarial Networks" (SAGAN)

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Miscellaneous

Bibliography

2023-liu-4.pdf: “Optimal Transport-Based Unsupervised Semantic Disentanglement: A Novel Approach for Efficient Image Editing in GANs”, Yunqi Liu, Xue Ouyang, Tian Jiang, Hongwei Ding, Xiaohui Cui

link-bibliography
https://arxiv.org/abs/2306.09346: “Rosetta Neurons: Mining the Common Units in a Model Zoo”, Amil Dravid, Yossi Gandelsman, Alexei A. Efros, Assaf Shocher

link-bibliography
https://arxiv.org/abs/2301.12811#sony: “SAN: Inducing Metrizability of GAN With Discriminative Normalized Linear Layer”, Yuhta Takida, Masaaki Imaizumi, Takashi Shibuya, Chieh-Hsin Lai, Toshimitsu Uesaka, Naoki Murata, Yuki Mitsufuji

link-bibliography
2022-wang-2.pdf: “Generalizing Factorization of GANs by Characterizing Convolutional Layers”, Yuehui Wang, Qing Wang, Dongyu Zhang

link-bibliography
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

link-bibliography
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

link-bibliography
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

link-bibliography
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

link-bibliography
https://arxiv.org/abs/2105.05233#openai: “Diffusion Models Beat GANs on Image Synthesis”, Prafulla Dhariwal, Alex Nichol

link-bibliography
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

link-bibliography
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

link-bibliography
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

link-bibliography
https://arxiv.org/abs/2010.05315: “SMYRF: Efficient Attention Using Asymmetric Clustering”, Giannis Daras, Nikita Kitaev, Augustus Odena, Alexandros G. Dimakis

link-bibliography
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

link-bibliography
https://arxiv.org/abs/2002.12655: “A U-Net Based Discriminator for Generative Adversarial Networks”, Edgar Schönfeld, Bernt Schiele, Anna Khoreva

link-bibliography
https://arxiv.org/abs/2002.04724: “Improved Consistency Regularization for GANs”, Zhengli Zhao, Sameer Singh, Honglak Lee, Zizhao Zhang, Augustus Odena, Han Zhang

link-bibliography
https://www.artbreeder.com/: “Artbreeder”, Joel Simon

link-bibliography
https://arxiv.org/abs/1907.02544: “Large Scale Adversarial Representation Learning”, Jeff Donahue, Karen Simonyan

link-bibliography
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

link-bibliography