997篇-歷史最全生成對抗網路（GAN）論文串燒

來自專欄深度學習與NLP

什麼是GAN？（本文內容整理自網路）

GAN（Generative Adversarial Netwo，生成對抗網路）是用於無監督學習的機器學習模型，由Ian Goodfellow等人在2014年提出，由神經網路構成判別器和生成器構成，通過一種互相競爭的機制組成的一種學習框架。

卷積神經網路之父-Yann LeCun這樣評論GAN：

在我看來，最重要的是對抗訓練( GAN也稱為生成對抗網路)。這一想法最初是Ian Goodfellow在蒙特利爾大學讀書是提出的，他當時是Yoshua Bengio的學生(Yoshua Bengio先加入了Google Brain，最近有離職加入OpenAI )。在我看來，這一想法與正在被提出的各種變化，是最近十年來在ML中最有趣的想法。

GAN是一個非常強大的框架，這裡，我們主要整理了自2014年，GAN推出以來，一些優質的論文，分享給有需要的朋友。

（限於篇幅原因，本文主要列出前50篇GAN相關論文，文末附上完整且帶論文鏈接的list）

列表如下：

1. 3C-GAN: AN CONDITION-CONTEXT-COMPOSITE GENERATIVE ADVERSARIAL NETWORKS FOR GENERATING IMAGES SEPARATELY

2018/1 ICLR2018 3C-GAN

2. 3D conditional generative adversarial networks for high-quality PET image estimation at low dose

2018/7 Medical: Reconstruction New

3. 3D Consistent Biventricular Myocardial Segmentation Using Deep Learning for Mesh Generation

2018/3 New, 3D

4. 3D Medical Image Synthesis using Generative Adversarial Networks

2017/ Medical: Synthersize Medical

5. 3D Object Reconstruction from a Single Depth View with Adversarial Learning?

2017/8 Applied Vision 3D-RecGAN

6. 3D Reconstruction of Incomplete Archaeological Objects Using a Generative Adversary Network

2017/11 ORGAN

8. 3D Shape Induction from 2D Views of Multiple Objects

2016/12 3D Object generation PrGAN Citation: 9

9. 3D-Scene-GAN: Three-dimensional Scene Reconstruction with Generative Adversarial Networks

2018/2 ICLR2018

10. A Classification-Based Perspective on GAN Distributions

2018/1 ICLR2018

11. A Classification-Based Perspective on GAN Distributions?

2017/11 Theory & Machine Learning Citation: 1

12. A conditional adversarial network for semantic segmentation of brain tumor

2018/2 Medical: Segmentation New

13. A Connection between Generative Adversarial Networks, Inverse Reinforcement Learning, and Energy-Based Models?

2016/11 Theory & Machine Learning Citation: 16

14. A Deep Generative Adversarial Architecture for Network-Wide Spatial-Temporal Traffic State Estimation

2018/1 None

15. A Deep Predictive Coding Network for Learning Latent Representations

2018/3 New, Bio

16. A General Retraining Framework for Scalable Adversarial Classification?

2016/4 Theory & Machine Learning Citation: 6

17. A Generalized Active Learning Approach for Unsupervised Anomaly Detection

2018/5 New

18. A generative adversarial framework for positive-unlabeled classification

2017/11 GPU

19. A Generative Model for Volume Rendering

2017/10 Medical: Volume Rendering Applied Other

20. A Hybrid Model for Identity Obfuscation by Face Replacement

2018/4 New

21. A Multi-Discriminator CycleGAN for Unsupervised Non-Parallel Speech Domain Adaptation

2018/4 New

22. A Novel Approach to Artistic Textual Visualization via GAN?

2017/10 Applied Vision GAN-ATV

23. A Self-Training Method for Semi-Supervised GANs

2018/1 ICLR2018

24. A Solvable High-Dimensional Model of GAN

2018/5 New

25. A step towards procedural terrain generation with GANs?

2017/7 Applied Vision

26. A Study into the similarity in generator and discriminator in GAN architecture

2018/2 None

27. A Study of Cross-domain Generative Models applied to Cartoon Series?

2017/9

28. A survey of image synthesis and editing with generative adversarial networks

2017/12 Medical: Synthersize New

29. A Variational Inequality Perspective on Generative Adversarial Nets

2018/2 None

30. A-Fast-RCNN: Hard Positive Generation via Adversary for Object Detection?

2017/4 Object Detection Citation: 12

31. ABC-GAN: Adaptive Blur and Control for improved training stability of Generative Adversarial Networks

2017/8 ABC-GAN Stars: 2

32. Abnormal Event Detection in Videos using Generative Adversarial Nets?

2017/8 Applied Vision

33. Accelerated Magnetic Resonance Imaging by Adversarial Neural Network

2017/9 Medical: Reconstruction

34. Accelerating Science with?Generative?Adversarial?Networks: An Application to 3D Particle Showers in Multilayer Calorimeters

2018/1 Medical: Reconstruction New

35. Activation Maximization Generative Adversarial Nets

2017/3 Theory & Machine Learning AM-GAN

36. Activation Maximization Generative Adversarial Nets

2018/1 ICLR2018

37. ACtuAL: Actor-Critic Under Adversarial Learning

2017/11 ACtuAL

38. AdaGAN: Boosting Generative Models?

2017/1 Ensemble, Theory & Machine Learning AdaGAN Citation: 19

39. Adaptive template generation for amyloid PET using a deep learning approach

2018/5 Medical: Synthersize New

40. Addressing Challenging Place Recognition Tasks using Generative Adversarial Networks?

2017/9

41. Adversarial Attacks on Neural Network Policies?

2017/2 Citation: 21

42. Adversarial Autoencoders?

2015/11 Theory & Machine Learning AAE Citation: 163 Stars: 130

43. Adversarial Data Programming: Using GANs to Relax the Bottleneck of Curated Labeled Data

2018/3 New

44. Adversarial Deep Structural Networks for Mammographic Mass Segmentation

2016/12 BioarXiv

45. Adversarial Deep Structural Networks for Mammographic Mass Segmentation?

2016/12 Semantic Segmentation Citation: 7

46. Adversarial Deep Structured Nets for Mass Segmentation from Mammograms

2017/10 Medical: Segmentation Stars: 13

47. Adversarial Discriminative Domain Adaptation?

2017/2 Theory & Machine Learning Citation: 52

48. Adversarial examples for generative models

2017/2 Adversarial Examples (Defense vs Attack)

49. Adversarial Examples for Semantic Segmentation and Object Detection?

2017/7 Citation: 17

50. Adversarial Examples Generation and Defense Based on Generative Adversarial Network

2017/ Adversarial Examples (Defense vs Attack)

完整論文列表下載地址

鏈接: https://pan.baidu.com/s/1KM1a17VZ2UrmClNCLLjChg

密碼: y6a6

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