The VLFeat open source library implements popular computer vision algorithms specializing in image understanding and local features extraction and matching. Algorithms include Fisher Vector, VLAD, SIFT, MSER, k-means, hierarchical k-means, agglomerative information bottleneck, SLIC superpixels, quick shift superpixels, large scale SVM training, and many others. It is written in C for efficiency and compatibility, with interfaces in MATLAB for ease of use, and detailed documentation throughout. It supports Windows, Mac OS X, and Linux. The latest version of VLFeat is 0.9.21.




Example applications


 Author = {A. Vedaldi and B. Fulkerson},
 Title = {{VLFeat}: An Open and Portable Library
          of Computer Vision Algorithms},
 Year  = {2008},
 Howpublished = {\url{http://www.vlfeat.org/}}


PASCAL2 credits Yandex                                                                credits UCLA Vision Lab Oxford VGG.


8/1/2018 VLFeat 0.9.21 released
Maintenance release. Fixed vl_argparse to be compatible with MatConvNet. Fixed the binaries for recent versions of macOS.
14/1/2015 VLFeat 0.9.20 released
Maintenance release. Bugfixes.
12/9/2014 MatConvNet
Looking for an easy-to-use package to work with deep convolutional neural networks in MATLAB? Check out our new MatConvNet toolbox!