生成对抗网络原理及代码解析,还介绍了神经网络的基础知识,对于GAN是什么,能做什么进行深入解析和科普。

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1.LOGO 生成对抗网络代码解析及原理 互联网新技术在线教育领航者

2.GAN LOGO • GAN简介 • GAN预备知识 • GAN网络实战分析 • 生成手写数字 demo分析 • 常见其他网络和改进策略 互联网新技术在线教育领航者

3.GAN 背景 LOGO Ian Goodfellow Generative Adversarial Networks(arxiv:https://arxiv.org/abs/1406.2661) Yann LeCun称为"过去十年机器学习界最有趣的idea" Generative:生成式模型 Adversarial: 采取对抗的策略 Networks: 网络(不一定是深度学习) 互联网新技术在线教育领航者

4.GAN 背景 LOGO • 3D-ED-GAN - Shape Inpainting using 3D Generative Adversarial Network and Recurrent Convolutional Networks iGAN - Generative Visual Manipulation on the Natural Image Manifold (github) • 3D-GAN - Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling(github) • Improved GAN - Improved Techniques for Training GANs (github) • 3D-IWGAN - Improved Adversarial Systems for 3D Object Generation and Reconstruction (github) • In2I - In2I : Unsupervised Multi-Image-to-Image Translation Using Generative Adversarial Networks • 3D-RecGAN - 3D Object Reconstruction from a Single Depth View with Adversarial Learning (github) • InfoGAN - InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets (github) • ABC-GAN - ABC-GAN: Adaptive Blur and Control for improved training stability of Generative Adversarial Networks (github) • IRGAN - IRGAN: A Minimax Game for Unifying Generative and Discriminative Information Retrieval models • ABC-GAN - GANs for LIFE: Generative Adversarial Networks for Likelihood Free Inference • Iterative-GAN - Two Birds with One Stone: Iteratively Learn Facial Attributes with GANs (github) • AC-GAN - Conditional Image Synthesis With Auxiliary Classifier GANs • IVE-GAN - IVE-GAN: Invariant Encoding Generative Adversarial Networks • acGAN - Face Aging With Conditional Generative Adversarial Networks • iVGAN - Towards an Understanding of Our World by GANing Videos in the Wild (github) • ACtuAL - ACtuAL: Actor-Critic Under Adversarial Learning • IWGAN - On Unifying Deep Generative Models • AdaGAN - AdaGAN: Boosting Generative Models • KBGAN - KBGAN: Adversarial Learning for Knowledge Graph Embeddings • AE-GAN - AE-GAN: adversarial eliminating with GAN • KGAN - KGAN: How to Break The Minimax Game in GAN • AEGAN - Learning Inverse Mapping by Autoencoder based Generative Adversarial Nets • l-GAN - Representation Learning and Adversarial Generation of 3D Point Clouds https://github.com/hindupuravinash/the-gan-zoo • AffGAN - Amortised MAP Inference for Image Super-resolution • LAGAN - Learning Particle Physics by Example: Location-Aware Generative Adversarial Networks for Physics Synthesis • AL-CGAN - Learning to Generate Images of Outdoor Scenes from Attributes and Semantic Layouts • LAPGAN - Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks (github) • ALI - Adversarially Learned Inference • LD-GAN - Linear Discriminant Generative Adversarial Networks • AlignGAN - AlignGAN: Learning to Align Cross-Domain Images with Conditional Generative Adversarial Networks • LDAN - Label Denoising Adversarial Network (LDAN) for Inverse Lighting of Face Images • AM-GAN - Activation Maximization Generative Adversarial Nets • LeakGAN - Long Text Generation via Adversarial Training with Leaked Information • AnoGAN - Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Discovery • LeGAN - Likelihood Estimation for Generative Adversarial Networks • ARAE - Adversarially Regularized Autoencoders for Generating Discrete Structures (github) • LGAN - Global versus Localized Generative Adversarial Nets • ARDA - Adversarial Representation Learning for Domain Adaptation • LR-GAN - LR-GAN: Layered Recursive Generative Adversarial Networks for Image Generation • ARIGAN - ARIGAN: Synthetic Arabidopsis Plants using Generative Adversarial Network • LS-GAN - Loss-Sensitive Generative Adversarial Networks on Lipschitz Densities • ArtGAN - ArtGAN: Artwork Synthesis with Conditional Categorial GANs • LSGAN - Least Squares Generative Adversarial Networks • AttGAN - Arbitrary Facial Attribute Editing: Only Change What You Want • MAD-GAN - Multi-Agent Diverse Generative Adversarial Networks • AttnGAN - AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks • MAGAN - MAGAN: Margin Adaptation for Generative Adversarial Networks • b-GAN - Generative Adversarial Nets from a Density Ratio Estimation Perspective • MalGAN - Generating Adversarial Malware Examples for Black-Box Attacks Based on GAN • Bayesian GAN - Deep and Hierarchical Implicit Models (github) • MaliGAN - Maximum-Likelihood Augmented Discrete Generative Adversarial Networks • Bayesian GAN - Bayesian GAN • MARTA-GAN - Deep Unsupervised Representation Learning for Remote Sensing Images • BCGAN - Bayesian Conditional Generative Adverserial Networks • McGAN - McGan: Mean and Covariance Feature Matching GAN • BCGAN - Bidirectional Conditional Generative Adversarial networks • MD-GAN - Learning to Generate Time-Lapse Videos Using Multi-Stage Dynamic Generative Adversarial Networks • BEGAN - BEGAN: Boundary Equilibrium Generative Adversarial Networks • MDGAN - Mode Regularized Generative Adversarial Networks • BGAN - Binary Generative Adversarial Networks for Image Retrieval (github) • MedGAN - Generating Multi-label Discrete Electronic Health Records using Generative Adversarial Networks • BiGAN - Adversarial Feature Learning • MGAN - Precomputed Real-Time Texture Synthesis with Markovian Generative Adversarial Networks (github) • BS-GAN - Boundary-Seeking Generative Adversarial Networks • MGGAN - Multi-Generator Generative Adversarial Nets • C-RNN-GAN - C-RNN-GAN: Continuous recurrent neural networks with adversarial training (github) • MIX+GAN - Generalization and Equilibrium in Generative Adversarial Nets (GANs) • CaloGAN - CaloGAN: Simulating 3D High Energy Particle Showers in Multi-Layer Electromagnetic Calorimeters with Generative Adversarial Networks (github) • MLGAN - Metric Learning-based Generative Adversarial Network • CAN - CAN: Creative Adversarial Networks, Generating Art by Learning About Styles and Deviating from Style Norms • MMD-GAN - MMD GAN: Towards Deeper Understanding of Moment Matching Network (github) • CatGAN - Unsupervised and Semi-supervised Learning with Categorical Generative Adversarial Networks • MMGAN - MMGAN: Manifold Matching Generative Adversarial Network for Generating Images • CatGAN - CatGAN: Coupled Adversarial Transfer for Domain Generation • MoCoGAN - MoCoGAN: Decomposing Motion and Content for Video Generation (github) • CausalGAN - CausalGAN: Learning Causal Implicit Generative Models with Adversarial Training • MPM-GAN - Message Passing Multi-Agent GANs • CC-GAN - Semi-Supervised Learning with Context-Conditional Generative Adversarial Networks (github) • MuseGAN - MuseGAN: Symbolic-domain Music Generation and Accompaniment with Multi-track Sequential Generative Adversarial Networks • CDcGAN - Simultaneously Color-Depth Super-Resolution with Conditional Generative Adversarial Network • MV-BiGAN - Multi-view Generative Adversarial Networks • CGAN - Conditional Generative Adversarial Nets • OptionGAN - OptionGAN: Learning Joint Reward-Policy Options using Generative Adversarial Inverse Reinforcement Learning • CGAN - Controllable Generative Adversarial Network • ORGAN - Objective-Reinforced Generative Adversarial Networks (ORGAN) for Sequence Generation Models • Chekhov GAN - An Online Learning Approach to Generative Adversarial Networks • ORGAN - 3D Reconstruction of Incomplete Archaeological Objects Using a Generative Adversary Network • CM-GAN - CM-GANs: Cross-modal Generative Adversarial Networks for Common Representation Learning • PAN - Perceptual Adversarial Networks for Image-to-Image Transformation • CoAtt-GAN - Are You Talking to Me? Reasoned Visual Dialog Generation through Adversarial Learning • PassGAN - PassGAN: A Deep Learning Approach for Password Guessing • CoGAN - Coupled Generative Adversarial Networks • Perceptual GAN - Perceptual Generative Adversarial Networks for Small Object Detection • ConceptGAN - Learning Compositional Visual Concepts with Mutual Consistency • PGAN - Probabilistic Generative Adversarial Networks • Conditional cycleGAN - Conditional CycleGAN for Attribute Guided Face Image Generation • Pip-GAN - Pipeline Generative Adversarial Networks for Facial Images Generation with Multiple Attributes • constrast-GAN - Generative Semantic Manipulation with Contrasting GAN • pix2pix - Image-to-Image Translation with Conditional Adversarial Networks (github) • Context-RNN-GAN - Contextual RNN-GANs for Abstract Reasoning Diagram Generation • PixelGAN - PixelGAN Autoencoders • Coulomb GAN - Coulomb GANs: Provably Optimal Nash Equilibria via Potential Fields • Pose-GAN - The Pose Knows: Video Forecasting by Generating Pose Futures • Cover-GAN - Generative Steganography with Kerckhoffs' Principle based on Generative Adversarial Networks • PPGN - Plug & Play Generative Networks: Conditional Iterative Generation of Images in Latent Space • Cramèr GAN - The Cramer Distance as a Solution to Biased Wasserstein Gradients • PrGAN - 3D Shape Induction from 2D Views of Multiple Objects • crVAE-GAN - Channel-Recurrent Variational Autoencoders • PSGAN - Learning Texture Manifolds with the Periodic Spatial GAN • CS-GAN - Improving Neural Machine Translation with Conditional Sequence Generative Adversarial Nets • PS²-GAN - High-Quality Facial Photo-Sketch Synthesis Using Multi-Adversarial Networks • CVAE-GAN - CVAE-GAN: Fine-Grained Image Generation through Asymmetric Training • RankGAN - Adversarial Ranking for Language Generation • CycleGAN - Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks (github) • RCGAN - Real-valued (Medical) Time Series Generation with Recurrent Conditional GANs • D2GAN - Dual Discriminator Generative Adversarial Nets • RefineGAN - Compressed Sensing MRI Reconstruction with Cyclic Loss in Generative Adversarial Networks • DAGAN - Data Augmentation Generative Adversarial Networks • RenderGAN - RenderGAN: Generating Realistic Labeled Data • DAN - Distributional Adversarial Networks • ResGAN - Generative Adversarial Network based on Resnet for Conditional Image Restoration • DCGAN - Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks(github) • RNN-WGAN - Language Generation with Recurrent Generative Adversarial Networks without Pre-training(github) • DeblurGAN - DeblurGAN: Blind Motion Deblurring Using Conditional Adversarial Networks (github) • RPGAN - Stabilizing GAN Training with Multiple Random Projections (github) • DeliGAN - DeLiGAN : Generative Adversarial Networks for Diverse and Limited Data (github) • RTT-GAN - Recurrent Topic-Transition GAN for Visual Paragraph Generation • DiscoGAN - Learning to Discover Cross-Domain Relations with Generative Adversarial Networks • RWGAN - Relaxed Wasserstein with Applications to GANs • DistanceGAN - One-Sided Unsupervised Domain Mapping • SAD-GAN - SAD-GAN: Synthetic Autonomous Driving using Generative Adversarial Networks • DM-GAN - Dual Motion GAN for Future-Flow Embedded Video Prediction • SalGAN - SalGAN: Visual Saliency Prediction with Generative Adversarial Networks (github) • DNA-GAN - DNA-GAN: Learning Disentangled Representations from Multi-Attribute Images • SBADA-GAN - From source to target and back: symmetric bi-directional adaptive GAN • DR-GAN - Representation Learning by Rotating Your Faces • SD-GAN - Semantically Decomposing the Latent Spaces of Generative Adversarial Networks • DRAGAN - How to Train Your DRAGAN (github) • SEGAN - SEGAN: Speech Enhancement Generative Adversarial Network • DRPAN - Discriminative Region Proposal Adversarial Networks for High-Quality Image-to-Image Translation • SeGAN - SeGAN: Segmenting and Generating the Invisible • DSP-GAN - Depth Structure Preserving Scene Image Generation • SegAN - SegAN: Adversarial Network with Multi-scale L1 Loss for Medical Image Segmentation • DTN - Unsupervised Cross-Domain Image Generation • SeqGAN - SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient (github) • DualGAN - DualGAN: Unsupervised Dual Learning for Image-to-Image Translation • SGAN - Texture Synthesis with Spatial Generative Adversarial Networks • Dualing GAN - Dualing GANs • SGAN - Stacked Generative Adversarial Networks (github) • EBGAN - Energy-based Generative Adversarial Network • SGAN - Steganographic Generative Adversarial Networks • ED//GAN - Stabilizing Training of Generative Adversarial Networks through Regularization • SimGAN - Learning from Simulated and Unsupervised Images through Adversarial Training • EGAN - Enhanced Experience Replay Generation for Efficient Reinforcement Learning • SketchGAN - Adversarial Training For Sketch Retrieval • ExprGAN - ExprGAN: Facial Expression Editing with Controllable Expression Intensity • SL-GAN - Semi-Latent GAN: Learning to generate and modify facial images from attributes • f-GAN - f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization • SN-GAN - Spectral Normalization for Generative Adversarial Networks (github) • FF-GAN - Towards Large-Pose Face Frontalization in the Wild • Sobolev GAN - Sobolev GAN • FIGAN - Frame Interpolation with Multi-Scale Deep Loss Functions and Generative Adversarial Networks • Softmax-GAN - Softmax GAN • Fila-GAN - Synthesizing Filamentary Structured Images with GANs • Splitting GAN - Class-Splitting Generative Adversarial Networks • Fisher GAN - Fisher GAN • SRGAN - Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network 互联网新技术在线教育领航者 • • Flow-GAN - Flow-GAN: Bridging implicit and prescribed learning in generative models FSEGAN - Exploring Speech Enhancement with Generative Adversarial Networks for Robust Speech Recognition • • SS-GAN - Semi-supervised Conditional GANs ss-InfoGAN - Guiding InfoGAN with Semi-Supervision • FTGAN - Hierarchical Video Generation from Orthogonal Information: Optical Flow and Texture • SSGAN - SSGAN: Secure Steganography Based on Generative Adversarial Networks • GAMN - Generative Adversarial Mapping Networks • SSL-GAN - Semi-Supervised Learning with Context-Conditional Generative Adversarial Networks • GAN - Generative Adversarial Networks (github) • ST-GAN - Style Transfer Generative Adversarial Networks: Learning to Play Chess Differently • GAN-ATV - A Novel Approach to Artistic Textual Visualization via GAN • StackGAN - StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks • GAN-CLS - Generative Adversarial Text to Image Synthesis (github) • StarGAN - StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation(github)

5.GAN能做什么? LOGO https://arxiv.org/pdf/1701.00160.pdf Lotter, W., Kreiman, G., and Cox, D. (2015). Unsupervised learning of visual structure using predictive generative networks. arXiv preprint arXiv:1511.06380 . 互联网新技术在线教育领航者

6.GAN能做什么? LOGO https://arxiv.org/pdf/1701.00160.pdf Ledig, C., Theis, L., Huszar, F., Caballero, J., Aitken, A. P., Tejani, A., Totz, J., Wang, Z., and Shi, W. (2016). Photo-realistic single image super-resolution using a generative adversarial network. CoRR, abs/1609.04802. 互联网新技术在线教育领航者

7.超分辨率科普 LOGO SRCNN Chao Dong, Chen Change Loy, Kaiming He, Xiaoou Tang. Learning a Deep Convolutional Network for Image Super-Resolution, in Proceedings of European Conference on Computer Vision (ECCV), 2014 互联网新技术在线教育领航者

8.GAN能做什么? LOGO https://arxiv.org/pdf/1701.00160.pdf https://www.youtube.com/watch?v=9c4z6YsBGQ0 互联网新技术在线教育领航者

9.GAN能做什么? LOGO https://arxiv.org/pdf/1701.00160.pdf Isola, P., Zhu, J.-Y., Zhou, T., and Efros, A. A. (2016). Image-to-image transla- tion with conditional adversarial networks. arXiv preprint arXiv:1611.07004 . 互联网新技术在线教育领航者

10.GAN能做什么? LOGO Videos http://web.mit.edu/vondrick/tinyvideo/ http://carlvondrick.com/tinyvideo/ 互联网新技术在线教育领航者

11.GAN能做什么? LOGO 互联网新技术在线教育领航者

12.GAN能做什么? starGAN LOGO http://cn.arxiv.org/pdf/1711.09020.pdf 互联网新技术在线教育领航者

13.GAN LOGO • GAN简介 • GAN预备知识 • GAN网络实战分析 • 生成手写数字 demo分析 • 常见其他网络和改进策略 互联网新技术在线教育领航者

14.神经网络科普 LOGO 互联网新技术在线教育领航者

15.神经网络科普 网络设计 LOGO 神经网络常见层(食材种类) 网络配置 网络训练流程(炒菜流程) • 全连接层 • 损失函数 • 预训练模型(高汤) • 激活层 • 优化器 • 训练流程 • BN层 • 激活函数 • 数据预处理 • Dropout层 • 性能评估 • 数据增强 • 卷积层 • 初始化方法 • … • 池化层 • 正则项 • 循环层RNN • … • Embedding层 • Merge层 • … 互联网新技术在线教育领航者

16.神经网络科普 全连接层 LOGO http://www.jianshu.com/p/88bb976ccbd9 互联网新技术在线教育领航者

17.神经网络科普 激活层 LOGO Sigmoid tanh ReLU Leaky ReLU 互联网新技术在线教育领航者 http://www.cnblogs.com/rgvb178/p/6055213.html

18.神经网络科普 反向传播 LOGO https://zhuanlan.zhihu.com/p/23270674 互联网新技术在线教育领航者

19.神经网络科普 优化器选择 LOGO https://www.jiqizhixin.com/articles/7c1ed66d-6742-43cc-9f47-89cd8cb5d9c0 互联网新技术在线教育领航者

20.神经网络科普 卷积层 LOGO 互联网新技术在线教育领航者

21.神经网络科普 卷积层 LOGO 互联网新技术在线教育领航者

22.神经网络科普 卷积层 LOGO 互联网新技术在线教育领航者

23.神经网络科普 卷积层 LOGO 互联网新技术在线教育领航者

24.神经网络科普 池化层 LOGO pooling 层的运算方法基本是和卷积层是一样的。 输入:n*c*w0*h0 输出:n*c*w1*h1 和卷积层的区别就是其中的 c 保持不变 w1=(w0+2*pad-kernel_size)/stride+1; h1=(h0+2*pad-kernel_size)/stride+1; 互联网新技术在线教育领航者

25.神经网络科普 常用解决套路 LOGO 互联网新技术在线教育领航者

26.神经网络科普 图像问题基本套路 LOGO 互联网新技术在线教育领航者

27.GAN LOGO • GAN简介 • GAN预备知识 • GAN网络实战分析 • 生成手写数字 demo分析 • 常见其他网络和改进策略 互联网新技术在线教育领航者

28.GAN 玩法 LOGO Generative Adversarial Nets 互联网新技术在线教育领航者

29.GAN 换种思路分析 LOGO GAN的思路:一个生成器,一个判别器 生成器G 判别器D GoodFellow的论文证明了GAN 全局最小点的充分必要条件是: 互联网新技术在线教育领航者 可以以假乱真了