2021年8月60篇GAN/对抗论文汇总

桃扇骨 2022-09-10 00:27 183阅读 0赞

等你着陆！【GAN生成对抗网络】知识星球

[**超100篇！CVPR 2020最全GAN论文梳理！**][100_CVPR 2020_GAN]**  **

**[2021年7月100篇GAN/对抗论文汇总][2021_7_100_GAN]**

**[2021年6月100篇GAN/对抗论文汇总][2021_6_100_GAN]**

**[2021年5月80篇GAN/对抗论文汇总][2021_5_80_GAN]**

**[2021年4月90篇GAN/对抗论文汇总][2021_4_90_GAN]**

**[2021年3月87篇GAN/对抗论文汇总][2021_3_87_GAN]**

**[2021年2月70篇GAN/对抗论文汇总][2021_2_70_GAN]**

**[2021年1月50篇GAN/对抗论文汇总][2021_1_50_GAN]**

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**[2020年10月80篇GAN/对抗论文汇总][2020_10_80_GAN]**

**[2020年9月70篇GAN/对抗论文汇总][2020_9_70_GAN]**

[**2020年8月60篇GAN/对抗论文汇总**][2020_8_60_GAN]

[**2020年7月90篇GAN论文汇总**][2020_7_90_GAN]

**[2020年6月100篇最新GAN论文汇总][2020_6_100_GAN]**

**[2020年5月60篇GAN论文汇总][2020_5_60_GAN]**

**[2020年4月份70多篇GAN论文！][2020_4_70_GAN]**

[**2020年3月至今90多篇GAN论文！**][2020_3_90_GAN]

[**2020年2月50多篇GAN论文！**][2020_2_50_GAN]

**[2020年1月部分GAN论文清单][2020_1_GAN] **

001  (2021-08-31) Eyes Tell All  Irregular Pupil Shapes Reveal GAN-generated Faces

https://arxiv.org/pdf/2109.00162.pdf

002  (2021-08-31) Quantization of Generative Adversarial Networks for Efficient Inference  a Methodological Study

https://arxiv.org/pdf/2108.13996.pdf

003  (2021-08-31) InSeGAN  A Generative Approach to Segmenting Identical Instances in Depth Images

https://arxiv.org/pdf/2108.13865.pdf

004  (2021-08-30) Enlisting 3D Crop Models and GANs for More Data Efficient and Generalizable Fruit Detection

https://arxiv.org/pdf/2108.13344.pdf

005  (2021-08-30) An Introduction to Variational Inference

https://arxiv.org/pdf/2108.13083.pdf

006  (2021-08-29) RetroGAN  A Cyclic Post-Specialization System for Improving Out-of-Knowledge and Rare Word Representations

https://arxiv.org/pdf/2108.12941.pdf

007  (2021-08-29) Layout-to-Image Translation with Double Pooling Generative Adversarial Networks

https://arxiv.org/pdf/2108.12900.pdf

008  (2021-08-28) Stagewise Unsupervised Domain Adaptation with Adversarial Self-Training for Road Segmentation of Remote Sensing Images

https://arxiv.org/pdf/2108.12611.pdf

009  (2021-08-26) Stop Throwing Away Discriminators  Re-using Adversaries for Test-Time Training

https://arxiv.org/pdf/2108.12280.pdf

010  (2021-08-26) Can the Transformer Be Used as a Drop-in Replacement for RNNs in Text-Generating GANs

https://arxiv.org/pdf/2108.12275.pdf

011  (2021-08-26) Re-using Adversarial Mask Discriminators for Test-time Training under Distribution Shifts

https://arxiv.org/pdf/2108.11926.pdf

012  (2021-08-25) Multi-Attributed and Structured Text-to-Face Synthesis

https://arxiv.org/pdf/2108.11100.pdf

013  (2021-08-24) DU-GAN  Generative Adversarial Networks with Dual-Domain U-Net Based Discriminators for Low-Dose CT Denoising

https://arxiv.org/pdf/2108.10772.pdf

014  (2021-08-24) A generative adversarial approach to facilitate archival-quality histopathologic diagnoses from frozen tissue ps

https://arxiv.org/pdf/2108.10550.pdf

015  (2021-08-23) Adaptable GAN Encoders for Image Reconstruction via Multi-type Latent Vectors with Two-scale Attentions

https://arxiv.org/pdf/2108.10201.pdf

016  (2021-08-11) Effective and Privacy preserving Tabular Data Synthesizing

https://arxiv.org/pdf/2108.10064.pdf

017  (2021-08-20) Cascade Watchdog  A Multi-tiered Adversarial Guard for Outlier Detection

https://arxiv.org/pdf/2108.09375.pdf

018  (2021-08-20) Zoom Enhance  Measuring Surveillance GAN Up-sampling

https://arxiv.org/pdf/2108.09285.pdf

019  (2021-08-20) ReGenMorph  Visibly Realistic GAN Generated Face Morphing Attacks by Attack Re-generation

https://arxiv.org/pdf/2108.09130.pdf

020  (2021-08-20) Indoor Scene Generation from a Collection of Semantic-Segmented Depth Images

https://arxiv.org/pdf/2108.09022.pdf

021  (2021-08-20) Dual Projection Generative Adversarial Networks for Conditional Image Generation

https://arxiv.org/pdf/2108.09016.pdf

022  (2021-08-19) Towards Vivid and Diverse Image Colorization with Generative Color Prior

https://arxiv.org/pdf/2108.08826.pdf

023  (2021-08-18) Scarce Data Driven Deep Learning of Drones via Generalized Data Distribution Space

https://arxiv.org/pdf/2108.08244.pdf

024  (2021-08-18) Unsupervised Image Generation with Infinite Generative Adversarial Networks

https://arxiv.org/pdf/2108.07975.pdf

025  (2021-08-17) FACIAL  Synthesizing Dynamic Talking Face with Implicit Attribute Learning

https://arxiv.org/pdf/2108.07938.pdf

026  (2021-08-17) Fed-TGAN  Federated Learning Framework for Synthesizing Tabular Data

https://arxiv.org/pdf/2108.07927.pdf

027  (2021-08-20) Intrinsic-Extrinsic Preserved GANs for Unsupervised 3D Pose Transfer

https://arxiv.org/pdf/2108.07520.pdf

028  (2021-08-17) Transferring Knowledge with Attention Distillation for Multi-Domain Image-to-Image Translation

https://arxiv.org/pdf/2108.07466.pdf

029  (2021-08-18) DRB-GAN  A Dynamic ResBlock Generative Adversarial Network for Artistic Style Transfer

https://arxiv.org/pdf/2108.07379.pdf

030  (2021-08-16) Structure-Aware Feature Generation for Zero-Shot Learning

https://arxiv.org/pdf/2108.07032.pdf

031  (2021-08-26) Online Multi-Granularity Distillation for GAN Compression

https://arxiv.org/pdf/2108.06908.pdf

032  (2021-08-14) A Survey on GAN Acceleration Using Memory Compression Technique

https://arxiv.org/pdf/2108.06626.pdf

033  (2021-08-14) Transfer Learning from an Artificial Radiograph-landmark Dataset for Registration of the Anatomic Skull Model to Dual Fluoroscopic X-ray Images

https://arxiv.org/pdf/2108.06466.pdf

034  (2021-08-13) A Generative Adversarial Framework for Optimizing Image Matting and Harmonization Simultaneously

https://arxiv.org/pdf/2108.06087.pdf

035  (2021-08-12) MISS GAN  A Multi-IlluStrator Style Generative Adversarial Network for image to illustration translation

https://arxiv.org/pdf/2108.05693.pdf

036  (2021-08-11) Welch-GAN  Generating realistic photoplethysmography signal from frequency-domain for atrial fibrillation detection

https://arxiv.org/pdf/2108.05272.pdf

037  (2021-08-10) Interpreting Generative Adversarial Networks for Interactive Image Generation

https://arxiv.org/pdf/2108.04896.pdf

038  (2021-07-21) Creating synthetic meteorology satellite visible light images during night based on GAN method

https://arxiv.org/pdf/2108.04330.pdf

039  (2021-08-7) GANmapper  geographical content filling

https://arxiv.org/pdf/2108.04232.pdf

040  (2021-08-9) A Streamwise GAN Vocoder for Wideband Speech Coding at Very Low Bit Rate

https://arxiv.org/pdf/2108.04051.pdf

041  (2021-08-9) FA-GAN  Fused Attentive Generative Adversarial Networks for MRI Image Super-Resolution

https://arxiv.org/pdf/2108.03920.pdf

042  (2021-08-9) Sinogram Denoise Based on Generative Adversarial Networks

https://arxiv.org/pdf/2108.03903.pdf

043  (2021-08-14) GAN Computers Generate Arts  A Survey on Visual Arts Music and Literary Text Generation using Generative Adversarial Network

https://arxiv.org/pdf/2108.03857.pdf

044  (2021-08-8) EVGen  Adversarial Networks for Learning Electric Vehicle Charging Loads and Hidden Representations

https://arxiv.org/pdf/2108.03762.pdf

045  (2021-08-7) Learning Foveated Reconstruction to Preserve Perceived Image Statistics

https://arxiv.org/pdf/2108.03499.pdf

046  (2021-08-6) SMOTified-GAN for class imbalanced pattern classification problems

https://arxiv.org/pdf/2108.03235.pdf

047  (2021-08-13) Disentangled Lifespan Face Synthesis

https://arxiv.org/pdf/2108.02874.pdf

048  (2021-08-5) Sketch Your Own GAN

https://arxiv.org/pdf/2108.02774.pdf

049  (2021-08-5) BOSS  Bidirectional One-Shot Synthesis of Adversarial Examples

https://arxiv.org/pdf/2108.02756.pdf

050  (2021-08-5) Instance Similarity Learning for Unsupervised Feature Representation

https://arxiv.org/pdf/2108.02721.pdf

051  (2021-08-4) Unsupervised Detection of Lung Nodules in Chest Radiography Using Generative Adversarial Networks

https://arxiv.org/pdf/2108.02233.pdf

052  (2021-08-4) MRI to PET Cross-Modality Translation using Globally and Locally Aware GAN (GLA-GAN) for Multi-Modal Diagnosis of Alzheimer's Disease

https://arxiv.org/pdf/2108.02160.pdf

053  (2021-08-4) Semi-supervised Conditional GAN for Simultaneous Generation and Detection of Phishing URLs  A Game theoretic Perspective

https://arxiv.org/pdf/2108.01852.pdf

054  (2021-08-5) Categorical EHR Imputation with Generative Adversarial Nets

https://arxiv.org/pdf/2108.01701.pdf

055  (2021-08-3) Image Augmentation Using a Task Guided Generative Adversarial Network for Age Estimation on Brain MRI

https://arxiv.org/pdf/2108.01659.pdf

056  (2021-08-3) The Devil is in the GAN  Defending Deep Generative Models Against Backdoor Attacks

https://arxiv.org/pdf/2108.01644.pdf

057  (2021-08-3) A Benchmarking Initiative for Audio-Domain Music Generation Using the Freesound Loop Dataset

https://arxiv.org/pdf/2108.01576.pdf

058  (2021-08-2) DarkGAN  Exploiting Knowledge Distillation for Comprehensible Audio Synthesis with GANs

https://arxiv.org/pdf/2108.01216.pdf

059  (2021-08-2) PSA-GAN  Progressive Self Attention GANs for Synthetic Time Series

https://arxiv.org/pdf/2108.00981.pdf

060  (2021-08-4) I2V-GAN  Unpaired Infrared-to-Visible Video Translation

https://arxiv.org/pdf/2108.00913.pdf

061  (2021-08-2) Information Stealing in Federated Learning Systems Based on Generative Adversarial Networks

https://arxiv.org/pdf/2108.00701.pdf

062  (2021-08-2) Learning who is in the market from time series  market participant discovery through adversarial calibration of multi-agent simulators

https://arxiv.org/pdf/2108.00664.pdf

063  (2021-08-1) Synthetic Active Distribution System Generation via Unbalanced Graph Generative Adversarial Network

https://arxiv.org/pdf/2108.00599.pdf

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[100_CVPR 2020_GAN]: http://mp.weixin.qq.com/s?__biz=MzU5MTgzNzE0MA%3D%3D&chksm=fe29a94cc95e205ae880cb9518cb16a54c0abde69e5a8654f7fedf70a0cc990775265bf28a1c&idx=1&mid=2247486455&scene=21&sn=94156f53845cdf07e859e343862be745#wechat_redirect
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[2021_6_100_GAN]: http://mp.weixin.qq.com/s?__biz=MzU5MTgzNzE0MA%3D%3D&chksm=fe2a462dc95dcf3be7db595f51e5f067bcbb74026ce9d0545dea2f16b139913d6dcb8be223c1&idx=1&mid=2247492758&scene=21&sn=6e7bff7b3e6e95c15a7e789bfcd298b6#wechat_redirect
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[2020_1_GAN]: http://mp.weixin.qq.com/s?__biz=MzU5MTgzNzE0MA%3D%3D&chksm=fe29a0dac95e29cc6801bc1a09be8853b370aefb59183947d0672e0989a4db2086d1dcaacf62&idx=1&mid=2247484001&scene=21&sn=a623d066459cb3dd01b6998da947fbc6#wechat_redirect
[GAN]: http://mp.weixin.qq.com/s?__biz=MzU5MTgzNzE0MA%3D%3D&chksm=fe29bf4bc95e365d4f53676d3aa2b80299375e55f9bab3bc7f8ad9405e7ada61d7ac00abb4bf&idx=1&mid=2247491056&scene=21&sn=535829ad04b094f59b2b38eb85cdbb38#wechat_redirect
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[CVPR 2021_GAN 1]: http://mp.weixin.qq.com/s?__biz=MzU5MTgzNzE0MA%3D%3D&chksm=fe29bfe4c95e36f275332b31b993532b98d52acc76d26c15e2321de4cf52141510bee3ff96af&idx=1&mid=2247490911&scene=21&sn=671926492c3b36e3350db4963f7fcb16#wechat_redirect
[GAN_StyleGAN]: http://mp.weixin.qq.com/s?__biz=MzU5MTgzNzE0MA%3D%3D&chksm=fe29bedbc95e37cd709f583372918478ad8d3cff5309a85f3a940e7c0356050278f89d7e1c79&idx=2&mid=2247490656&scene=21&sn=bbe156fef077f23263b57e506ad43314#wechat_redirect
[20_ StyleGAN]: http://mp.weixin.qq.com/s?__biz=MzU5MTgzNzE0MA%3D%3D&chksm=fe29b979c95e306f03b134809b16009d06aa0694b03da3368f84625de3700e6a56221d49d1bf&idx=1&mid=2247490498&scene=21&sn=324cfbbde362a728aa5336f4b200f7a3#wechat_redirect
[_ _Python]: http://mp.weixin.qq.com/s?__biz=MzU5MTgzNzE0MA%3D%3D&chksm=fe29abb6c95e22a04d1eb019f964c8ae97b2f3af98c22f730f5d5ed2aea9fdb320b00c688967&idx=2&mid=2247485709&scene=21&sn=55a51c98ab48f393ba305c082ba0e4fe#wechat_redirect
[_ _Think Python]: http://mp.weixin.qq.com/s?__biz=MzU5MTgzNzE0MA%3D%3D&chksm=fe29a418c95e2d0e9a3de46e0e4d1b8d4947154d8639418a511a3091300aa31699932046556e&idx=2&mid=2247485091&scene=21&sn=f569d5d70c2e6c9cc567fbc5147787a4#wechat_redirect
[_ _Pytorch]: http://mp.weixin.qq.com/s?__biz=MzU5MTgzNzE0MA%3D%3D&chksm=fe29aa78c95e236e380c9fd2ae79917d7451ccdd4803c5e6047a16f921d1b61d18efc79ada7c&idx=2&mid=2247485635&scene=21&sn=90608bce32fe353cf3c64b39e3406bc3#wechat_redirect
[_ _2020]: http://mp.weixin.qq.com/s?__biz=MzU5MTgzNzE0MA%3D%3D&chksm=fe29a4a4c95e2db2aab16bdcefa78795bbb7efbc70b533bb197d73f617558f2f8a523120c6e3&idx=2&mid=2247484959&scene=21&sn=563999cc8d48498beed00270844ceec4#wechat_redirect
[Link 1]: http://mp.weixin.qq.com/s?__biz=MzU5MTgzNzE0MA%3D%3D&chksm=fe29a4bac95e2dac758c4aac10a3aac49eb062bc0829d4ef2ebc8e6d5069d246385c5084a2b4&idx=1&mid=2247484929&scene=21&sn=523220858287ed3e6105919703c8e833#wechat_redirect
[_TensorFlow 2.0]: http://mp.weixin.qq.com/s?__biz=MzU5MTgzNzE0MA%3D%3D&chksm=fe29a5b0c95e2ca6599d4a91d5d40900566b7525de3dd85259e7a6c173aa26aa7ea3641d1aaf&idx=2&mid=2247485195&scene=21&sn=e3387067db29d1759755c6c2ea96c870#wechat_redirect
[Link 2]: http://mp.weixin.qq.com/s?__biz=MzU5MTgzNzE0MA%3D%3D&chksm=fe29aa8fc95e23993e057fb0dbe09f2810ea07184a439c173f404a7ab657cadcde3d24efa52a&idx=2&mid=2247485492&scene=21&sn=c4fb135de02cd52f06bc61b0e79476e4#wechat_redirect
[bad9ae1bd550cf3101924f40f6f1847c.png]: /images/20220829/11dd942389f0493991ca8623744ca917.png