WILLOW-ObjectClass Dataset V1.0
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This dataset contains images and their feature annotations used in our ICCV'13 paper [1].  

The dataset contains object class images from Caltech-256 [2] (Face, Duck, and Wine bottle) 
and PASCAL VOC2007 [3] (Motorbike and Car) datasets. The images of these classes are 
selected such that each class contains at least 40 images with different instances.
Currently, it consists of 109 Face, 50 Duck, 66 Wine bottle, 40 Motorbike, and 40 Car images. 

Each image has an annotation file with 10 distinctive points, which are consistent for the same class. 
In [1], these annotations are used to evaluate the accuracy of matching with local feature detectors.  

If you use this dataset, please cite:
[1] Minsu Cho, Karteek Alahari, Jean Ponce
Learning Graphs to Match
Proceedings of the IEEE International Conference on Computer Vision, 2013.

If you have any questions, please contact: Minsu Cho (minsu.cho@ens.fr).


Additional References
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[2] Griffin, G. Holub, AD. Perona, P. The Caltech 256. Caltech Technical Report.

[3] Everingham, M. and Van Gool, L. and Williams, C. K. I. and Winn, J. and Zisserman, A. 
    The PASCAL Visual Object Classes Challenge 2007 (VOC2007) Results.