A Review: Generative Adversarial Networks
暂无分享,去创建一个
[1] Max Welling,et al. Auto-Encoding Variational Bayes , 2013, ICLR.
[2] Jaakko Lehtinen,et al. Progressive Growing of GANs for Improved Quality, Stability, and Variation , 2017, ICLR.
[3] Tara N. Sainath,et al. FUNDAMENTAL TECHNOLOGIES IN MODERN SPEECH RECOGNITION Digital Object Identifier 10.1109/MSP.2012.2205597 , 2012 .
[4] Dimitris N. Metaxas,et al. StackGAN: Text to Photo-Realistic Image Synthesis with Stacked Generative Adversarial Networks , 2016, 2017 IEEE International Conference on Computer Vision (ICCV).
[5] Adam Finkelstein,et al. PairedCycleGAN: Asymmetric Style Transfer for Applying and Removing Makeup , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[6] Tatjana Chavdarova,et al. SGAN: An Alternative Training of Generative Adversarial Networks , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[7] Yann LeCun,et al. Deep multi-scale video prediction beyond mean square error , 2015, ICLR.
[8] Jeff Donahue,et al. Large Scale GAN Training for High Fidelity Natural Image Synthesis , 2018, ICLR.
[9] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[10] Aaron C. Courville,et al. Improved Training of Wasserstein GANs , 2017, NIPS.
[11] Antonio Torralba,et al. Generating Videos with Scene Dynamics , 2016, NIPS.
[12] Raymond Y. K. Lau,et al. Least Squares Generative Adversarial Networks , 2016, 2017 IEEE International Conference on Computer Vision (ICCV).
[13] Yoshua Bengio,et al. Generative Adversarial Nets , 2014, NIPS.
[14] Ran He,et al. Beyond Face Rotation: Global and Local Perception GAN for Photorealistic and Identity Preserving Frontal View Synthesis , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[15] David Berthelot,et al. BEGAN: Boundary Equilibrium Generative Adversarial Networks , 2017, ArXiv.
[16] Yann LeCun,et al. Energy-based Generative Adversarial Network , 2016, ICLR.
[17] Zachary Chase Lipton. A Critical Review of Recurrent Neural Networks for Sequence Learning , 2015, ArXiv.
[18] Pieter Abbeel,et al. InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets , 2016, NIPS.
[19] Simon Osindero,et al. Conditional Generative Adversarial Nets , 2014, ArXiv.
[20] Byoung-Tak Zhang,et al. Generating Images Part by Part with Composite Generative Adversarial Networks , 2016, ArXiv.
[21] Koray Kavukcuoglu,et al. Pixel Recurrent Neural Networks , 2016, ICML.
[22] Christopher M. Bishop,et al. A New Framework for Machine Learning , 2008, WCCI.
[23] Nojun Kwak,et al. MC-GAN: Multi-conditional Generative Adversarial Network for Image Synthesis , 2018, BMVC.
[24] Soumith Chintala,et al. Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks , 2015, ICLR.
[25] Guo-Jun Qi,et al. Loss-Sensitive Generative Adversarial Networks on Lipschitz Densities , 2017, International Journal of Computer Vision.
[26] Zhe Gan,et al. AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[27] Jie Zhang,et al. PDP: parallel dynamic programming , 2017, IEEE CAA J. Autom. Sinica.
[28] J. Nash. Two-Person Cooperative Games , 1953 .
[29] Alexei A. Efros,et al. Image-to-Image Translation with Conditional Adversarial Networks , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[30] Rob Fergus,et al. Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks , 2015, NIPS.
[31] Zhe Gan,et al. Generating Text via Adversarial Training , 2016 .
[32] Jung-Woo Ha,et al. StarGAN: Unified Generative Adversarial Networks for Multi-domain Image-to-Image Translation , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[33] Wei Xiong,et al. Learning to Generate Time-Lapse Videos Using Multi-stage Dynamic Generative Adversarial Networks , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[34] Léon Bottou,et al. Wasserstein GAN , 2017, ArXiv.
[35] 拓海 杉山,et al. “Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks”の学習報告 , 2017 .
[36] Augustus Odena,et al. Semi-Supervised Learning with Generative Adversarial Networks , 2016, ArXiv.
[37] Eder Santana,et al. Learning a Driving Simulator , 2016, ArXiv.