Self-Attention GAN

Introduced by Zhang et al. in Self-Attention Generative Adversarial Networks

The Self-Attention Generative Adversarial Network, or SAGAN, allows for attention-driven, long-range dependency modeling for image generation tasks. Traditional convolutional GANs generate high-resolution details as a function of only spatially local points in lower-resolution feature maps. In SAGAN, details can be generated using cues from all feature locations. Moreover, the discriminator can check that highly detailed features in distant portions of the image are consistent with each other.

Source: Self-Attention Generative Adversarial Networks

Latest Papers

PAPER DATE
not-so-BigGAN: Generating High-Fidelity Images on a Small Compute Budget
Seungwook HanAkash SrivastavaCole HurwitzPrasanna SattigeriDavid D. Cox
2020-09-09
Neural Crossbreed: Neural Based Image Metamorphosis
Sanghun ParkKwanggyoon SeoJunyong Noh
2020-09-02
Instance Selection for GANs
Terrance DeVriesMichal DrozdzalGraham W. Taylor
2020-07-30
Interpolating GANs to Scaffold Autotelic Creativity
Ziv EpsteinOcéane BoulaisSkylar GordonMatt Groh
2020-07-21
Differentiable Augmentation for Data-Efficient GAN Training
| Shengyu ZhaoZhijian LiuJi LinJun-Yan ZhuSong Han
2020-06-18
Training Generative Adversarial Networks with Limited Data
| Tero KarrasMiika AittalaJanne HellstenSamuli LaineJaakko LehtinenTimo Aila
2020-06-11
Learning disconnected manifolds: a no GANs land
Ugo TanielianThibaut IssenhuthElvis DohmatobJeremie Mary
2020-06-08
Big GANs Are Watching You: Towards Unsupervised Object Segmentation with Off-the-Shelf Generative Models
| Andrey VoynovStanislav MorozovArtem Babenko
2020-06-08
A U-Net Based Discriminator for Generative Adversarial Networks
Edgar Schonfeld Bernt Schiele Anna Khoreva
2020-06-01
Network Fusion for Content Creation with Conditional INNs
Robin RombachPatrick EsserBjörn Ommer
2020-05-27
GANSpace: Discovering Interpretable GAN Controls
| Erik HärkönenAaron HertzmannJaakko LehtinenSylvain Paris
2020-04-06
Evolving Normalization-Activation Layers
| Hanxiao LiuAndrew BrockKaren SimonyanQuoc V. Le
2020-04-06
Feature Quantization Improves GAN Training
| Yang ZhaoChunyuan LiPing YuJianfeng GaoChangyou Chen
2020-04-05
BigGAN-based Bayesian reconstruction of natural images from human brain activity
Kai QiaoJian ChenLinyuan WangChi ZhangLi TongBin Yan
2020-03-13
A U-Net Based Discriminator for Generative Adversarial Networks
| Edgar SchönfeldBernt SchieleAnna Khoreva
2020-02-28
Improved Consistency Regularization for GANs
Zhengli ZhaoSameer SinghHonglak LeeZizhao ZhangAugustus OdenaHan Zhang
2020-02-11
Reconstructing Natural Scenes from fMRI Patterns using BigBiGAN
Milad MozafariLeila ReddyRufin VanRullen
2020-01-31
Random Matrix Theory Proves that Deep Learning Representations of GAN-data Behave as Gaussian Mixtures
Mohamed El Amine SeddikCosme LouartMohamed TamaazoustiRomain Couillet
2020-01-21
CNN-generated images are surprisingly easy to spot... for now
| Sheng-Yu WangOliver WangRichard ZhangAndrew OwensAlexei A. Efros
2019-12-23
Detecting GAN generated errors
Xiru ZhuFengdi CheTianzi YangTzuyang YuDavid MegerGregory Dudek
2019-12-02
LOGAN: Latent Optimisation for Generative Adversarial Networks
| Yan WuJeff DonahueDavid BalduzziKaren SimonyanTimothy Lillicrap
2019-12-02
Your Local GAN: Designing Two Dimensional Local Attention Mechanisms for Generative Models
| Giannis DarasAugustus OdenaHan ZhangAlexandros G. Dimakis
2019-11-27
Semantic Hierarchy Emerges in Deep Generative Representations for Scene Synthesis
| Ceyuan YangYujun ShenBolei Zhou
2019-11-21
Improving sample diversity of a pre-trained, class-conditional GAN by changing its class embeddings
| Qi LiLong MaiMichael A. AlcornAnh Nguyen
2019-10-10
Attribute Manipulation Generative Adversarial Networks for Fashion Images
Kenan E. Ak Joo Hwee Lim Jo Yew Tham Ashraf A. Kassim
2019-10-01
Adversarial Video Generation on Complex Datasets
Aidan ClarkJeff DonahueKaren Simonyan
2019-07-15
Large Scale Adversarial Representation Learning
| Jeff DonahueKaren Simonyan
2019-07-04
Improved Precision and Recall Metric for Assessing Generative Models
| Tuomas KynkäänniemiTero KarrasSamuli LaineJaakko LehtinenTimo Aila
2019-04-15
High-Fidelity Image Generation With Fewer Labels
| Mario LucicMichael TschannenMarvin RitterXiaohua ZhaiOlivier BachemSylvain Gelly
2019-03-06
Unsupervised Image-to-Image Translation with Self-Attention Networks
| Taewon KangKwang Hee Lee
2019-01-24
Discriminator Rejection Sampling
| Samaneh AzadiCatherine OlssonTrevor DarrellIan GoodfellowAugustus Odena
2018-10-16
Metropolis-Hastings view on variational inference and adversarial training
Kirill NeklyudovEvgenii EgorovPavel ShvechikovDmitry Vetrov
2018-10-16
Large Scale GAN Training for High Fidelity Natural Image Synthesis
| Andrew BrockJeff DonahueKaren Simonyan
2018-09-28
Generative Adversarial Network with Spatial Attention for Face Attribute Editing
| Gang ZhangMeina KanShiguang ShanXilin Chen
2018-09-01
Self-Attention Generative Adversarial Networks
| Han ZhangIan GoodfellowDimitris MetaxasAugustus Odena
2018-05-21

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