Supercharging Style Transfer Wednesday, October 26, 2016 Posted by Vincent Dumoulin*, Jonathon Shlens and Manjunath Kudlur, Google Brain Team Pastiche. A French word, it designates a work of art that imitates the style of another one (not to be con…
Deep Learning & Art: Neural Style Transfer Welcome to the second assignment of this week. In this assignment, you will learn about Neural Style Transfer. This algorithm was created by Gatys et al. (2015) (https://arxiv.org/abs/1508.06576). In this as…
Andrew Ng deeplearning courese-4:Convolutional Neural Network Convolutional Neural Networks: Step by Step Convolutional Neural Networks: Application Residual Networks Autonomous driving - Car detection YOLO Face Recognition for the Happy House Art: N…
Perceptual Losses for Real-Time Style Transfer and Super-Resolution and Super-Resolution 论文笔记 ECCV 2016 摘要: 许多经典问题可以看做是 图像转换问题(image transformation tasks).本文所提出的方法来解决的图像转换问题,是以监督训练的方式,训练一个前向传播的网络,利用的就是图像像素级之间的误差.这种方法在测试的时候非常有效,因为仅仅需要一次前向传播即可.但是,像素级的误…
第四周:Special applications: Face recognition & Neural style transfer 什么是人脸识别?(What is face recognition?) 欢迎来到第四周,即这门课卷积神经网络课程的最后一周.到目前为止,你学了很多卷积神经网络的知识.我这周准备向你展示一些重要的卷积神经网络的特殊应用,我们将从人脸识别开始,之后讲神经风格迁移,你将有机会在编程作业中实现这部分内容,创造自己的艺术作品. 让我们先从人脸识别开始,我这里有一个有意思的演…
Text Style Transfer主要是指Non-Parallel Data条件下的,具体的paper list见: https://github.com/fuzhenxin/Style-Transfer-in-Text Delete, Retrieve, Generate: A Simple Approach to Sentiment and Style Transfer (NAACL 2018) Transforming a sentence to alter a specific at…
网络风格迁移 作者:无用 本文通过学习吴恩达视频所做笔记 目录 简介 可视化卷积层 构建风格迁移网络 一.网络风格迁移简介 二.可视化卷积层 可视化深层卷积网络???这个问题我看过一篇文章,我会在后补上 本网络共有5个卷积层,每个层的卷积核所检测的对象都不一致 第一层 一直重复直到第五层结束.层数往后,其检测的对象越明确. 三.构建风格迁移网络 First we define the cost function.which means the degree of similary between…
Face Recognition for the Happy House Welcome to the first assignment of week 4! Here you will build a face recognition system. Many of the ideas presented here are from FaceNet. In lecture, we also talked about DeepFace. Face recognition problems com…
[解释] This allows us to learn to predict a person’s identity using a softmax output unit, where the number of classes equals the number of persons in the database plus 1 (for the final “not in database” class). 上述选项错误的原因: 1.plus 1的解释错误: 将某人的照片放进卷积神经网络…
IEEE International Conference on Computer Vision, ICCV 2017, Venice, Italy, October 22-29, 2017. IEEE Computer Society 2017, ISBN 978-1-5386-1032-9 Oral Session 1 Globally-Optimal Inlier Set Maximisation for Simultaneous Camera Pose and Feature Corre…
A PyTorch Tools, best practices & Styleguide 中文版:PyTorch代码规范最佳实践和样式指南 This is not an official style guide for PyTorch. This document summarizes best practices from more than a year of experience with deep learning using the PyTorch framework. Note th…
Basic usage: th neural_style.lua -style_image <image.jpg> -content_image <image.jpg> OpenCL usage with NIN Model (This requires you download the NIN Imagenet model files as described above): th neural_style.lua -style_image examples/inputs/pic…
转自:http://blog.evjang.com/2017/01/nips2016.html Eric Jang Technology, A.I., Careers Monday, January 2, 2017 Summary of NIPS 2016 The 30th annual Neural Information Processing Systems (NIPS) conference took place in Barcelona…
CVPR2017 paper list Machine Learning 1 Spotlight 1-1A Exclusivity-Consistency Regularized Multi-View Subspace Clustering Xiaojie Guo, Xiaobo Wang, Zhen Lei, Changqing Zhang, Stan Z. Li Borrowing Treasures From the Wealthy: Deep Transfer Learning Thro…
转自:http://www.asimovinstitute.org/neural-network-zoo/ THE NEURAL NETWORK ZOO POSTED ON SEPTEMBER 14, 2016 BY FJODOR VAN VEEN With new neural network architectures popping up every now and then, it's hard to keep track of them all. Knowing all the a…
