The issus in Age Progression/Regression by Conditional Adversarial Autoencoder (CAAE)
The issus in Age Progression/Regression by Conditional Adversarial Autoencoder (CAAE)
Today I tried a new project named: Face-Aging-CAAE
Paper Name: Age Progression/Regression by Conditional Adversarial Autoencoder (CAAE)
Github: https://github.com/ZZUTK/Face-Aging-CAAE
But count some issues before I run the code successfully. Maybe it caused by the version of tensorflow.
1. TypeError: Expected int32, got list containing Tensors of type '_Message' instead.
2. ValueError: Only call 'sigmoid_cross_entropy_with_logits' with named arguments (labels=..., logits=..., ...)
3. ValueError: Variable E_conv0/w/Adam/ does not exist, or was not created with tf.get_variable(). Did you mean to set reuse=None in VarScope ?
The follow changes are needed for this code to solve above issues.
Then, you will see the process of training:
The issus in Age Progression/Regression by Conditional Adversarial Autoencoder (CAAE)的更多相关文章
- Learning Face Age Progression: A Pyramid Architecture of GANs-1-实现人脸老化
Learning Face Age Progression: A Pyramid Architecture of GANs Abstract 人脸年龄发展有着两个重要的需求,即老化准确性和身份持久性, ...
- image-to-image translation with conditional adversarial networks文献笔记
Image-to-Image Translation with Conditional Adversarial Networks (基于条件gan的图像转图像) 作者:Phillip Isola, J ...
- Learning Face Age Progression: A Pyramid Architecture of GANs
前言 作为IP模式识别的CNN初始模型是作为单纯判别式-模式识别存在的,并以此为基本模型扩展到各个方向.基本功能为图像判别模型,此后基于Loc+CNN的检测模型-分离式.end2end.以及MaskC ...
- Latent Representation Learning For Artificial Bandwidth Extension Using A Conditional Variational Auto-Encoder
博客作者:凌逆战 论文地址:https://ieeexplore.ieee.xilesou.top/abstract/document/8683611/ 地址:https://www.cnblogs. ...
- (Pixel2PixelGANs)Image-to-Image translation with conditional adversarial networks
Introduction 1. develop a common framework for all problems that are the task of predicting pixels f ...
- 《Image-to-Image Translation with Conditional Adversarial Networks》论文笔记
出处 CVPR2017 Motivation 尝试用条件GAN网络来做image translation,让网络自己学习图片到图片的映射函数,而不需要人工定制特征. Introduction 作者从不 ...
- Generative Adversarial Nets[content]
0. Introduction 基于纳什平衡,零和游戏,最大最小策略等角度来作为GAN的引言 1. GAN GAN开山之作 图1.1 GAN的判别器和生成器的结构图及loss 2. Condition ...
- Generative Adversarial Nets[CAAE]
本文来自<Age Progression/Regression by Conditional Adversarial Autoencoder>,时间线为2017年2月. 该文很有意思,是如 ...
- [转]GAN论文集
really-awesome-gan A list of papers and other resources on General Adversarial (Neural) Networks. Th ...
随机推荐
- python: numpy--函数 shape用法
http://blog.csdn.net/u010758410/article/details/71554224 shape函数是numpy.core.fromnumeric中的函数,它的功能是查看矩 ...
- 深度解读 AlphaGo 算法原理
http://blog.csdn.net/songrotek/article/details/51065143 http://blog.csdn.net/dinosoft/article/detail ...
- jQuery效果--show([speed,[easing],[fn]])和hide([speed,[easing],[fn]])
hide([speed,[easing],[fn]]) 概述 隐藏显示的元素 这个就是 'hide( speed, [callback] )' 的无动画版.如果选择的元素是隐藏的,这个方法将不会改变任 ...
- Python数据可视化-seaborn
详细介绍可以看seaborn官方API和example galler. 1 set_style( ) set( ) set_style( )是用来设置主题的,Seaborn有五个预设好的主题: d ...
- js三目学习
<script> var n=1; n>1?document.write('大于1哦'):document.write('小于或等于1哦') //n=n>1?document. ...
- loadRunner手动关联, web_reg_save_param_regexp()函数正则匹配字符,赋值给变量
loadRunner写脚本实现登录机票网站,手动关联,获取页面源码中特定字符 手动关联,就是通过函数获取某个步骤生成的字符,赋值给一个变量,这个变量可以作为接下来某个步骤的输入, 以便这个脚本能够在存 ...
- ATM取款机
package Tests; import java.io.BufferedReader;import java.io.File;import java.io.FileInputStream;impo ...
- Linux服务器---邮件服务openwebmail安装
安装openwebmail openwebmail提供了可视化的邮件管理系统,它运行在Apache环境下. 1.安装必备软件 [root@localhost ~]# yum install –y p ...
- 事务 c#
事务->:事务是恢复和并发控制的基本单位 ->事务具有四个特性:原子性.隔离性.一致性.持久性.这四个特性通常称为ACID Begin transaction/tran --开始事务 ...
- GROUP BY 和 ORDER BY 同时使用问题
GROUP BY 和 ORDER BY一起使用时,ORDER BY要在GROUP BY的后面.