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state-of-the-art implementations related to visual recognition and search

http://rogerioferis.com/VisualRecognitionAndSearch2014/Resources.html Source Code Non-exhaustive list of state-of-the-art implementations related to visual recognition and search. There is no warranty for the source code links below – use them at you…

Image Processing and Analysis_8_Edge Detection：Edge and line oriented contour detection State of the art ——2011

此主要讨论图像处理与分析.虽然计算机视觉部分的有些内容比如特 征提取等也可以归结到图像分析中来,但鉴于它们与计算机视觉的紧密联系,以 及它们的出处,没有把它们纳入到图像处理与分析中来.同样,这里面也有一些 也可以划归到计算机视觉中去.这都不重要,只要知道有这么个方法,能为自己 所用,或者从中得到灵感,这就够了. 8. Edge Detection 边缘检测也是图像处理中的一个基本任务.传统的边缘检测方法有基于梯度 算子,尤其是 Sobel 算子,以及经典的 Canny 边缘检测.到现在,Cann…

Convolutional Neural Networks for Visual Recognition

http://cs231n.github.io/   里面有很多相当好的文章 http://cs231n.github.io/convolutional-networks/ Table of Contents: Architecture Overview ConvNet Layers Convolutional Layer Pooling Layer Normalization Layer Fully-Connected Layer Converting Fully-Connected Laye…

大规模视觉识别挑战赛ILSVRC2015各团队结果和方法 Large Scale Visual Recognition Challenge 2015

Large Scale Visual Recognition Challenge 2015 (ILSVRC2015) Legend: Yellow background = winner in this task according to this metric; authors are willing to reveal the method White background = authors are willing to reveal the method Grey background…

论文笔记之： Bilinear CNN Models for Fine-grained Visual Recognition

Bilinear CNN Models for Fine-grained Visual Recognition CVPR 2015 本文提出了一种双线性模型( bilinear models),一种识别结构,该结构由两个特征提取器产生,两个输出是图像每一个位置的外积(outer product),然后进行 pool,得到最终的图像描述算子.这种结构可以对局部 pairwise feature interactions 以平移不变的方式进行建模.而且,可以产生不同的无序的文字描述,像 Fisher…

CNN for Visual Recognition (01)

CS231n: Convolutional Neural Networks for Visual Recognitionhttp://vision.stanford.edu/teaching/cs231n/syllabus.html 主要利用神经网络解决图像分类问题.…

【论文阅读】Deep Mixture of Diverse Experts for Large-Scale Visual Recognition

导读: 本文为论文<Deep Mixture of Diverse Experts for Large-Scale Visual Recognition>的阅读总结.目的是做大规模图像分类(>1000类),方法是混合多个小深度网络实现更多类的分类.本文从以下五个方面来对论文做个简要整理: 背景:简要介绍与本文方法提出的背景和独特性. 方法:介绍论文使用的大体方法. 细节:介绍论文中方法涉及到的问题及解决方案. 实验:实验结果和简要分析. 总结:论文主要特色和个人体会. 一.背景 1.目标…

目标检测--Spatial pyramid pooling in deep convolutional networks for visual recognition(PAMI, 2015)

Spatial pyramid pooling in deep convolutional networks for visual recognition 作者: Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun 引用: He, Kaiming, et al. "Spatial pyramid pooling in deep convolutional networks for visual recognition." IEEE…

A Theoretical Analysis of Feature Pooling in Visual Recognition

这篇是10年ICML的论文,但是它是从原理上来分析池化的原因,因为池化的好坏的确会影响到结果,比如有除了最大池化和均值池化,还有随机池化等等,在eccv14中海油在顶层加个空间金字塔池化的方法.可谓多种多样.本文主要研究了最大池化和均值池化本文的翻译还是烂尾,后面没动力了. A Theoretical Analysis of Feature Pooling in Visual Recognition Y-lan Boureau,Jean  ponce, yann LeCun 摘要:许多当前的视觉…

Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition

Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun  The 13th European Conference on Computer Vision (ECCV), 2014 声明:本文所有图片均来自原始文章,自己的理解也未必正确,请查看原图并拍砖 本文的两个亮点: 1. 多尺度训练CN…