Closed haoawesome closed 10 years ago
https://github.com/memect/hao/blob/master/awesome/computer-vision-dataset.md 计算机视觉数据集(computer vision dataset)汇总
http://www.computervisiononline.com/datasets 这是个计算机视觉数据集汇总,罗列了100多个数据集
丕子 Computer Vision Online http://t.cn/zjSJ8RZ | 转发(9)| 收藏| 评论(1) 2012-12-14 12:26来自微博 weibo.com http://www.weibo.com/1665335994/z9HhW83Zp
http://en.wikipedia.org/wiki/Category:Datasets_in_computer_vision
http://yann.lecun.com/exdb/mnist/ The MNIST database of handwritten digits, available from this page, has a training set of 60,000 examples, and a test set of 10,000 examples. It is a subset of a larger set available from NIST. The digits have been size-normalized and centered in a fixed-size image.
http://www.cs.toronto.edu/~kriz/cifar.html cifar10 The CIFAR-10 and CIFAR-100 are labeled subsets of the 80 million tiny images dataset. They were collected by Alex Krizhevsky, Vinod Nair, and Geoffrey Hinton. The CIFAR-10 dataset consists of 60000 32x32 colour images in 10 classes, with 6000 images per class. There are 50000 training images and 10000 test images.
http://en.wikipedia.org/wiki/Caltech_101 Caltech 101 is a data set of digital images created in September, 2003, compiled by Fei-Fei Li, Marco Andreetto, Marc 'Aurelio Ranzato and Pietro Perona at the California Institute of Technology. It is intended to facilitate Computer Vision research and techniques. It is most applicable to techniques involving recognition, classification, and categorization. Caltech 101 contains a total of 9146 images, split between 101 distinct objects (including faces, watches, ants, pianos, etc.) and a background category (for a total of 102 categories). Provided with the images are a set of annotations describing the outlines of each image, along with a Matlab script for viewing.
http://en.wikipedia.org/wiki/LabelMe LabelMe is a project created by the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) which provides a dataset of digital images with annotations. The dataset is dynamic, free to use, and open to public contribution. The most applicable use of LabelMe is in computer vision research. As of October 31, 2010, LabelMe has 187,240 images, 62,197 annotated images, and 658,992 labeled objects.
http://sourceforge.net/projects/oirds/ Overhead Imagery Research Data Set (OIRDS) - an annotated data library & tools to aid in the development of computer vision algorithms
facial recognition datasets
http://en.wikipedia.org/wiki/Comparison_of_facial_image_datasets
更多的数据集列表
http://clickdamage.com/sourcecode/cv_datasets.php
http://riemenschneider.hayko.at/vision/dataset/
http://homepages.inf.ed.ac.uk/rbf/CVonline/
http://www.nicta.com.au/research/projects/AutoMap/computer_vision_datasets
http://blog.sina.com.cn/s/blog_a5fdbf0101017qyv.html#bsh-24-206218261
@henglovelan
debug的博客
在做视频监控中,常常需要用到几个标准的测试数据库,有的时候不方便找,在这里我就给出2个经常用到的标准数据库的地址:
1、http://groups.inf.ed.ac.uk/vision/CAVIAR/CAVIARDATA1/,这个是英国的Edinburgh大学的数据库CAVIAR;
2、http://groups.inf.ed.ac.uk/vision/BEHAVEDATA/INTERACTIONS/,这个也是英国的Edinburgh大学的数据库BEHAVE;
[计算机视觉数据集不完全汇总] http://memect.co/SPa8n25 经典热点数据集: ImageNet,Flickr,MNIST 数据集目录: YACVID(200+),ComputerVisionOnline(100+),CVpapers(100+),CVOnline(100+),UIUC,UCSD,NICTA... 感谢 @丕子 @邹宇华 @李岩ICT人脸识别 @网路冷眼 @王威廉 @金连文 @数据堂 zhubenfulovepoem 推荐
http://www.weibo.com/5220650532/BoAbfmDPA?ref=
王威廉 :雅虎研究院的数据集汇总下载:http://t.cn/8F3RLwr 包括语言类数据,图与社交类数据,评分与分类数据,计算广告学数据,图像数据,竞赛数据,以及系统类的数据。
赞(28)| 转发(423)| 收藏| 评论(31) 2月26日19:03 http://weibo.com/1657470871/AyDkznp21
@网路冷眼 :【Yahoo实验室公开1亿Flickr图像和视频供研究之用】http://t.cn/RvTmAAA 这次公布的数据集可能是世界上最大的公开多媒体数据集之一,全部遵从Creative Commons许可。全部文件大约12GB,并包括元数据,可用Flickr API查询。获取地址:http://t.cn/Rvrbuad @蒋涛CSDN @孢子响马 @张栋_机器学习
金连文 :IAPR TC11的官网上有许多文档处理相关的数据集,例如联机及脱机手写数据、Text、自然场景的文档图像, 网址:http://t.cn/z8Aw8zT http://weibo.com/1548358505/A6Fp5d2se
http://blog.csdn.net/zhubenfulovepoem/article/details/7191794
@zhubenfulovepoem
以下是computer vision:algorithm and application计算机视觉算法与应用这本书中附录里关于计算机视觉的一些测试数据集和源码站点,我整理了下,加了点中文注解
请问 哪里有公路上的视频监控视角的行人数据集呢? 类似 VOCdevkit 里面的数据集
我再问点问题哦。。做图像识别需要大量的训练样本对呗,那网上有多少现成的样本呢?我就知道Mnist,cifar10这样很经典的样本集,还有就是ImageNet了。。。有没有人总结过,有哪些好用的免费样本集呢?我在做智能交通方面的图像识别,一般去哪里找相关的样本集呢?