A collection of resources on GAN Inversion: Interpreting the Latent Space of Pretrained Models.
Feedback and contributions are welcome!
If you think I have missed out on something (or) have any suggestions (papers, implementations and other resources), feel free to pull a request.
I have released the latex files. Please pull a request, open an issue, or send me an email if you find any inappropriate expressions of the survey.
markdown format:
**Here is the Paper Name.**<br>
*[Author 1](homepage), Author 2, and Author 3.*<br>
Conference or Journal Year. [[PDF](link)] [[Project](link)] [[Github](link)] [[Video](link)] [[Data](link)][Papers on Generative Modeling]
GAN Inversion: A Survey.
Weihao Xia, Yulun Zhang, Yujiu Yang, Jing-Hao Xue, Bolei Zhou, Ming-Hsuan Yang.
arxiv 2021. [PDF]
@article{xia2021survey,
author = {Xia, Weihao and Zhang, Yulun and Yang, Yujiu and Xue, Jing-Hao and Zhou, Bolei and Yang, Ming-Hsuan},
title = {GAN Inversion: A Survey},
journal={arXiv preprint arXiv: 2101.05278},
year={2021}
}StyleGAN2-Ada: Training Generative Adversarial Networks with Limited Data.
Tero Karras, Miika Aittala, Janne Hellsten, Samuli Laine, Jaakko Lehtinen, Timo Aila.
NeurIPS 2020. [PDF] [Github] [Steam StyleGAN2-ADA
]
StyleGAN2: Analyzing and Improving the Image Quality of StyleGAN.
Tero Karras, Samuli Laine, Miika Aittala, Janne Hellsten, Jaakko Lehtinen, Timo Aila.
CVPR 2020.
[PDF]
[Offical TF]
[PyTorch]
[Unoffical Tensorflow 2.0]
A Style-Based Generator Architecture for Generative Adversarial Networks.
Tero Karras, Samuli Laine, Timo Aila.
CVPR 2019. [PDF] [Offical TF]
Progressive Growing of GANs for Improved Quality, Stability, and Variation.
Tero Karras, Timo Aila, Samuli Laine, Jaakko Lehtinen.
ICLR 2018. [PDF] [Offical TF]
Exploring Adversarial Fake Images on Face Manifold.
Dongze Li, Wei Wang, Hongxing Fan, Jing Dong.
arxiv 2021. [PDF]
OSTeC: One-Shot Texture Completion.
Baris Gecer, Jiankang Deng, Stefanos Zafeiriou.
arxiv 2021. [PDF] [Github]
Improved StyleGAN Embedding: Where are the Good Latents?
Peihao Zhu, Rameen Abdal, Yipeng Qin, Peter Wonka.
arxiv 2020. [PDF]
Learning a Deep Reinforcement Learning Policy Over the Latent Space of a Pre-trained GAN for Semantic Age Manipulation.
Kumar Shubham, Gopalakrishnan Venkatesh, Reijul Sachdev, Akshi, Dinesh Babu Jayagopi, G. Srinivasaraghavan.
arxiv 2020. [PDF]
Lifting 2D StyleGAN for 3D-Aware Face Generation.
Yichun Shi, Divyansh Aggarwal, Anil K. Jain.
arxiv 2020. [PDF]
Navigating the GAN Parameter Space for Semantic Image Editing.
Anton Cherepkov, Andrey Voynov, Artem Babenko.
arxiv 2020. [PDF] [Github]
Augmentation-Interpolative AutoEncoders for Unsupervised Few-Shot Image Generation.
Davis Wertheimer, Omid Poursaeed, Bharath Hariharan.
arxiv 2020. [PDF]
Mask-Guided Discovery of Semantic Manifolds in Generative Models.
Mengyu Yang, David Rokeby, Xavier Snelgrove.
Workshop on Machine Learning for Creativity and Design (NeurIPS) 2020. [PDF] [Github]
Unsupervised Discovery of Disentangled Manifolds in GANs.
Yu-Ding Lu, Hsin-Ying Lee, Hung-Yu Tseng, Ming-Hsuan Yang.
arxiv 2020. [PDF]]
StyleSpace Analysis: Disentangled Controls for StyleGAN Image Generation.
Zongze Wu, Dani Lischinski, Eli Shechtman.
arxiv 2020. [PDF]
DeepLandscape: Adversarial Modeling of Landscape Videos.
E. Logacheva, R. Suvorov, O. Khomenko, A. Mashikhin, and V. Lempitsky.
ECCV 2020. [PDF] [Github] [Project]
Learning a Deep Reinforcement Learning Policy Over the Latent Space of a Pre-trained GAN for Semantic Age Manipulation.
Kumar Shubham, Gopalakrishnan Venkatesh, Reijul Sachdev, Akshi, Dinesh Babu Jayagopi, G. Srinivasaraghavan.
arxiv 2020. [PDF]
DeepI2I: Enabling Deep Hierarchical Image-to-Image Translation by Transferring from GANs.
yaxing wang, Lu Yu, Joost van de Weijer.
NeurIPS 2020. [PDF] [Github]
GAN Steerability without optimization.
Nurit Spingarn-Eliezer, Ron Banner, Tomer Michaeli.
arxiv 2020. [OpenReview] [PDF]
On The Inversion Of Deep Generative Models (When and How Can Deep Generative Models be Inverted?).
Aviad Aberdam, Dror Simon, Michael Elad.
ICLR 2021. [PDF] [OpenReview]
PIE: Portrait Image Embedding for Semantic Control.
A. Tewari, M. Elgharib, M. BR, F. Bernard, H-P. Seidel, P. Pérez, M. Zollhöfer, C.Theobalt.
SIGGRAPH Asia 2020. [PDF] [Project]
Encoding in Style: a StyleGAN Encoder for Image-to-Image Translation.
Elad Richardson, Yuval Alaluf, Or Patashnik, Yotam Nitzan, Yaniv Azar, Stav Shapiro, Daniel Cohen-Or.
arxiv 2020. [PDF] [Github] [Project]
Understanding the Role of Individual Units in a Deep Neural Network.
David Bau, Jun-Yan Zhu, Hendrik Strobelt, Agata Lapedriza, Bolei Zhou, Antonio Torralba.
National Academy of Sciences 2020. [PDF] [Github] [Project]
Unsupervised Image-to-Image Translation via Pre-trained StyleGAN2 Network.
Jialu Huang, Jing Liao, Sam Kwong.
arxiv 2020. [PDF]
SeFa: Closed-Form Factorization of Latent Semantics in GANs.
Yujun Shen, Bolei Zhou.
arxiv 2020. [PDF] [Github] [Project]
Collaborative Learning for Faster StyleGAN Embedding.
Shanyan Guan, Ying Tai, Bingbing Ni, Feida Zhu, Feiyue Huang, Xiaokang Yang.
arxiv 2020. [PDF]
Disentangling in Latent Space by Harnessing a Pretrained Generator.
Yotam Nitzan, Amit Bermano, Yangyan Li, Daniel Cohen-Or.
arxiv 2020. [PDF]
Face Identity Disentanglement via Latent Space Mapping.
Yotam Nitzan, Amit Bermano, Yangyan Li, Daniel Cohen-Or.
arxiv 2020. [PDF] [Github]
Transforming and Projecting Images into Class-conditional Generative Networks.
Minyoung Huh, Richard Zhang, Jun-Yan Zhu, Sylvain Paris, Aaron Hertzmann.
arxiv 2020. [PDF] [Github] [Project]
Interpreting the Latent Space of GANs via Correlation Analysis for Controllable Concept Manipulation.
Ziqiang Li, Rentuo Tao, Hongjing Niu, Bin Li.
arxiv 2020. [PDF]
GANSpace: Discovering Interpretable GAN Controls.
Erik Härkönen, Aaron Hertzmann, Jaakko Lehtinen, Sylvain Paris.
arxiv 2020. [PDF] [Github]
StyleFlow: Attribute-conditioned Exploration of StyleGAN-Generated Images using Conditional Continuous Normalizing Flows.
Rameen Abdal, Peihao Zhu, Niloy Mitra, Peter Wonka.
Siggraph Asia 2020. [PDF] [Github]
Rewriting a Deep Generative Model.
David Bau, Steven Liu, Tongzhou Wang, Jun-Yan Zhu, Antonio Torralba.
ECCV 2020. [PDF] [Github]
StyleGAN2 Distillation for Feed-forward Image Manipulation.
Yuri Viazovetskyi, Vladimir Ivashkin, Evgeny Kashin.
ECCV 2020. [PDF] [Github]
In-Domain GAN Inversion for Real Image Editing.
Jiapeng Zhu, Yujun Shen, Deli Zhao, Bolei Zhou.
ECCV 2020. [PDF] [Project] [Github]
Exploiting Deep Generative Prior for Versatile Image Restoration and Manipulation.
Xingang Pan, Xiaohang Zhan, Bo Dai, Dahua Lin, Chen Change Loy, Ping Luo.
ECCV 2020. [PDF] [Github]
On the "steerability" of generative adversarial networks.
Ali Jahanian, Lucy Chai, Phillip Isola.
ICLR 2020. [PDF] [Project]
Unsupervised Discovery of Interpretable Directions in the GAN Latent Space.
Andrey Voynov, Artem Babenko.
ICML 2020. [PDF] [Github]
Your Local GAN: Designing Two Dimensional Local Attention Mechanisms for Generative Models.
Giannis Daras, Augustus Odena, Han Zhang, Alexandros G. Dimakis.
CVPR 2020. [PDF]
A Disentangling Invertible Interpretation Network for Explaining Latent Representations.
Patrick Esser, Robin Rombach, Björn Ommer.
CVPR 2020. [PDF] [Project] [Github]
Editing in Style: Uncovering the Local Semantics of GANs.
Edo Collins, Raja Bala, Bob Price, Sabine Süsstrunk.
CVPR 2020. [PDF] [Github]
Image Processing Using Multi-Code GAN Prior.
Jinjin Gu, Yujun Shen, Bolei Zhou.
CVPR 2020. [PDF] [Project] [Github]
Interpreting the Latent Space of GANs for Semantic Face Editing.
Yujun Shen, Jinjin Gu, Xiaoou Tang, Bolei Zhou.
CVPR 2020. [PDF] [Project] [Github]
Image2StyleGAN++: How to Edit the Embedded Images?
Rameen Abdal, Yipeng Qin, Peter Wonka.
CVPR 2020. [PDF]
Semantic Photo Manipulation with a Generative Image Prior.
David Bau, Hendrik Strobelt, William Peebles, Jonas, Bolei Zhou, Jun-Yan Zhu, Antonio Torralba.
SIGGRAPH 2019. [PDF]
Image2StyleGAN: How to Embed Images Into the StyleGAN Latent Space?
Rameen Abdal, Yipeng Qin, Peter Wonka.
ICCV 2019. [PDF]
Seeing What a GAN Cannot Generate.
David Bau, Jun-Yan Zhu, Jonas Wulff, William Peebles, Hendrik Strobelt, Bolei Zhou, Antonio Torralba.
ICCV 2019. [PDF] [PDF]
GAN-based Projector for Faster Recovery with Convergence Guarantees in Linear Inverse Problems.
Ankit Raj, Yuqi Li, Yoram Bresler.
ICCV 2019. [PDF]
Inverting Layers of a Large Generator.
David Bau, Jun-Yan Zhu, Jonas Wulff, William Peebles, Hendrik Strobelt, Bolei Zhou, Antonio Torralba.
ICCV 2019. [PDF]
Task-Aware Compressed Sensing with Generative Adversarial Networks.
Maya Kabkab, Pouya Samangouei, Rama Chellappa.
AAAI 2018. [PDF]
Inverting The Generator Of A Generative Adversarial Network (II).
Antonia Creswell, Anil A Bharath.
TNNLS 2018. [PDF] [Github]
Invertibility of convolutional generative networks from partial measurements.
Fangchang Ma, Ulas Ayaz, Sertac Karaman.
NeurIPS 2018. [PDF] [Github]
Metrics for Deep Generative Models.
Nutan Chen, Alexej Klushyn, Richard Kurle, Xueyan Jiang, Justin Bayer, Patrick van der Smagt.
AISTATS 2018. [PDF]
Towards Understanding the Invertibility of Convolutional Neural Networks.
Anna C. Gilbert, Yi Zhang, Kibok Lee, Yuting Zhang, Honglak Lee.
IJCAI 2017. [PDF]
One Network to Solve Them All - Solving Linear Inverse Problems using Deep Projection Models.
J. H. Rick Chang, Chun-Liang Li, Barnabas Poczos, B. V. K. Vijaya Kumar, Aswin C. Sankaranarayanan.
ICCV 2017. [PDF]
Inverting The Generator Of A Generative Adversarial Network.
Antonia Creswell, Anil Anthony Bharath.
NIPSW 2016. [PDF]
Generative Visual Manipulation on the Natural Image Manifold.
Jun-Yan Zhu, Philipp Krähenbühl, Eli Shechtman, Alexei A. Efros.
ECCV 2016. [PDF]