PROGRESSIVE GROWING OF GANS FOR IMPROVED QUALITY, STABILITY, AND VARIATION,程序员大本营,技术文章内容聚合第一站。
中文名:GAN 的渐进式增长以提高质量、稳定性和变异性 本文介绍了一种新的生成对抗网络(GAN)的训练方法,名为“渐进式增长的GAN”(Progressive Growing of GANs ),其关键思想是逐步增加生成器和判别器的层数,从而在训练过程中逐步发现图像分布的大规模结构,并将注意力转移到越来越精细的细节上。这种方法不仅加快了训...
Progressive Growing of GANs for Improved Quality, Stability, and Variation Method Key Word: 对抗生成模型, AIGC, 博弈论 Function: 多样地生成高分辨率的逼真图片 Advantage: 相较其它GAN, 可以生成多样的高分率高质量图片(无鬼脸) Example 在CelebA人脸数字图片数据集上进行实验,可生成(1024,1024)大小的图片 ...
生成的图片的保持灵活性程度:现在有很多方法来估计它,例如:inception score、multi-scale structural similarity、birthday paradox、explicit tests(for the number of discrete modes discovered) gans存在一个问题,即它只能捕捉到训练数据集变化的子集。为了解决这个问题,Salimans等人(2016)提出了称为“minibatch discrimin...
简介:《Progressive Growing of GANs for Improved Quality, Stability, and Variation》-论文阅读笔记(一) 《Progressive Growing ofGANsfor Improved Quality, Stability, and Variation》-论文阅读笔记 论文结构 1.Introduction 2.Progressive growing of GANs ...
2 Progressive growing of GANs Our primary contribution is a training methodology for GANs where we start with low-resolution images, and then progressively increase the resolution by adding layers to the networks as visualized in Figure 1. This incremental nature allows the training to first ...
另外一个好处是减少了训练时间。随着GANs网络的渐进增长,大部分的迭代都在较低分辨率下完成,对比结果质量加快了2-6倍的速度,这都依赖最后的输出分辨率。 The idea of growing GANs progressively is related to the work of Wang et al. (2017), who use multiple discriminators that operate on different spatia...
论文链接:Progressive Growing of GANs for Improved Quality, Stability, and Variation 二、复现精度 参考官方开源的 pytorch 版本代码 https://github.com/facebookresearch/pytorch_GAN_zoo,基于 paddlepaddle 深度学习框架,对文献算法进行复现后,本项目达到的测试精度,如下表所示。 参考文献的最高精度为 CelebA MS-...
Progressive Growing of GANs for Improved Quality, Stability, and Variation论文阅读笔记,程序员大本营,技术文章内容聚合第一站。
PublishedasaconferencepaperatICLR2018 PROGRESSIVEGROWINGOFGANSFORIMPROVED QUALITY,STABILITY,ANDVARIATION TeroKarras NVIDIA {tkarras,taila,slaine,jlehtinen}@nvidia TimoAila NVIDIA SamuliLaine NVIDIA JaakkoLehtinen NVIDIAandAaltoUniversity ABSTRACT Wedescribeanewtrainingmethodologyforgenerativeadversarialnetworks.The key...