ROC(Receiver Operating Characteristic)曲线是以假正率(FP_rate)和真正率(TP_rate)为轴的曲线,ROC曲线下面的面积我们叫做AUC,如下图所示: 图片根据Paper:Learning from eImbalanced Data画出 其中: T P r a t e = T P P c TP_{rate}=\frac{TP}{P_c}TPrate=PcTP, F P r a t e =...
intra预测的过程被表述为一个基于学习的inpainting task,利用GAN的generator在已经解码的block的基础上对缺失的部分进行预测,充分利用邻域信息,可以更好的预测当前待编码单元。 使用提出的GAN方法对intra预测模块进行了重新设计,并进行了率失真操作(RDO),以在传统方法和GAN方法之间选择最佳方法,并附加一个标记。 在编码器...
下图(下)两个不同的generator能力不同,weak generaotr无法生出有意义的图片,而strong generator可以生出逼真的图片,但是两者的disciminator的loss都几乎为零,无区分度。 此图来自paper:Martin Arjovsky, Léon Bottou,Towards Principled Methods for Training Generative Adversarial Network Q:所以为什么discriminator的loss...
5、Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network 6、Image-to-Image Translation with Conditional Adversarial Networks 7、Chen, Xi, et al. “Infogan: Interpretable representation learning by information maximizing generative adversarial nets.” Advances in Neural Informati...
5、Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network 6、Image-to-Image Translation with Conditional Adversarial Networks 7、Chen, Xi, et al. “Infogan: Interpretable representation learning by information maximizing generative adversarial nets.” Advances in Neural Informati...
paper | Generative Adversarial Network-Based Intra Prediction for Video Coding 摘要 提出一种新的帧内预测方法,使用GAN来消除空间冗余。基于GAN的方法的方法使用更多的信息来产生更灵活的预测模式。帧内预测被建模为一个去瑕疵过程,使用GAN来充满重建帧中丢失的部分。GAN模型被加入到编码器和解码器中,与传统的预测...
machine-learningpytorchartificial-intelligencegenerative-adversarial-networkgenerative-model UpdatedAug 23, 2024 Python podgorskiy/ALAE Star3.5k Code Issues Pull requests [CVPR2020] Adversarial Latent Autoencoders pythonmachine-learningcomputer-visiondeep-learningneural-networkpaperpytorchgenerative-adversarial-network...
不出意外先给出github代码地址以及paper地址:Code|Paper 一、 模型结构介绍 Generative Network 上面两张图基本上描述了生产网络以及判别网络的结构,这里需要补充的是此网络的输入分别是一张图片的高清图片以及非高清图片。 1、生成网络模型结构及代码 生成网络主要通过将输入图片进行下采样卷积在进行上采样得到我们生成的...
presented a paper entitled “Generative Adversarial Nets”1 at the Neural Information Processing Systems conference (NeurIPS) in Montreal. The introduction of generative adversarial networks (or GANs, as they are more commonly known) is now regarded as a key turning point in the history of ...
Perceptual Generative Adversarial Networks for Small Object Detection 2017-07-11 19:47:46 CVPR 2017 This paper use GAN to handle the issue of small object detection which is a very hard problem in general object detection. As shown in the following figures, small object and large objects usuall...