转载链接:https://www.jianshu.com/p/4e5b3e652639 Szegedy在2015年发表了论文Rethinking the Inception Architecture for Computer Vision,该论文对之前的Inception结构提出了多种优化方法,来达到尽可能高效的利用计算资源的目的.作者认为随意增大Inception的复杂度,后果就是Inception的错误率很容易飙升,还会成倍的增加计算量,所以必须按照一套合理的规则来优化Inception结构…
https://arxiv.org/abs/1512.00567 Convolutional networks are at the core of most state-of-the-art computer vision solutions for a wide variety of tasks. Since 2014 very deep convolutional networks started to become mainstream, yielding substantial gai…
目录 0. paper link 1. Overview 2. Four General Design Principles 3. Factorizing Convolutions with Large Filter Size 3.1 Factorization into smaller convolutions 3.2. Spatial Factorization into Asymmetric Convolutions 4. Utility of Auxiliary Classifiers…
1. 论文思想 factorized convolutions and aggressive regularization. 本文给出了一些网络设计的技巧. 2. 结果 用5G的计算量和25M的参数.With an ensemble of 4 models and multi-crop evaluation, we report 3.5% top-5 error and 17.3% top-1 error. 3. Introduction scaling up convolution netwo…
WTF is computer vision? Posted Nov 13, 2016 by Devin Coldewey, Contributor Next Story Someone across the room throws you a ball and you catch it. Simple, right? Actually, this is one of the most complex processes we've ever attempted to compr…
Analyzing The Papers Behind Facebook's Computer Vision Approach Introduction You know that company called Facebook? Yeah, the one that has 1.6 billion people hooked on their website. Take all of the happy birthday posts, embarrassing pictures of you…
The picture above is funny. But for me it is also one of those examples that make me sad about the outlook for AI and for Computer Vision. What would it take for a computer to understand this image as you or I do? I challenge you to think explicitly…
http://www.themtank.org/a-year-in-computer-vision 部分中文翻译汇总:https://blog.csdn.net/chengyq116/article/details/78660521 The M Tank 编辑了一份报告<A Year in Computer Vision>,记录了 2016 至 2017 年计算机视觉领域的研究成果,对开发者和研究人员来说是不可多得的一份详细材料.虽然该文已经过去一年多的时间了,但是考虑到研究成果由理论到落地的…
In the 1960s, the legendary Stanford artificial intelligence pioneer, John McCarthy, famously gave a graduate student the job of “solving” computer vision as a summer project. It has occupied an entire community of academic researchers for the past 4…
As I walked through the large poster-filled hall at CVPR 2013, I asked myself, “Quo vadis Computer Vision?" (Where are you going, computer vision?) I see lots of papers which exploit last year’s ideas, copious amounts of incremental research, and an…
Capel, David, and Andrew Zisserman. "Computer vision applied to super resolution." Signal Processing Magazine, IEEE 20, no. 3 (2003): 75-86. 简介 超分辨率重建的目的是使用一组低分辨率的图像来估计一副高分辨率图像.重建主要通过两个步骤来完成:配准低分辨率的图片组到一个公共的坐标系,然后使用图像的生成模型(generative image model…
Graph Cut and Its Application in Computer Vision 原文出处: http://lincccc.blogspot.tw/2011/04/graph-cut-and-its-application-in.html 现在好像需要代理才能访问了... 网络流算法最初用于解决流网络的优化问题,比如水管网络.通信传输和城市的车流等.Graph cut作为其中一类最常见的算法,用于求解流网络的最小割,即寻找一个总容量最小的边集合,去掉这个集合中的所有边将阻断这个网…
ECCV 2012 (http://eccv2012.unifi.it/program/tutorials/) Vision Applications on Mobile using OpenCVGary Bradski (Industrial Perception), Victor Eruhimov (Itseez), Vadim Pisarevsky (Itseez)http://opencv.org/eccv2012.htmlhttp://eccv2012.unifi.it/program…
计算机视觉中的边缘检测 边缘检测是计算机视觉中最重要的概念之一.这是一个很直观的概念,在一个图像上运行图像检测应该只输出边缘,与素描比较相似.我的目标不仅是清晰地解释边缘检测是怎样工作的,同时也提供一个新而又容易的方法只需要最小工作来明显地提高边缘检测. 通过获得这些边缘,许多计算机算法才得以有可能实现,因为在一个场景中边缘包含着绝大部分(至少很多)的信息. 举个例子,我们都记得 Windows XP 的那个绿色小山坡和蓝色天空的背景. 当我们的大脑试图去理解这个场景时,我们知道这是草地,看…
https://opencv.org/ OpenCV (Open Source Computer Vision Library) is released under a BSD license and hence it’s free for both academic and commercial use. It has C++, C, Python and Java interfaces and supports Windows, Linux, Mac OS, iOS and Android.…
