Skip to content

Code for Ragav Venkatesan, Parag Shridhar Chandakkar, Baoxin Li "Simpler non-parametric methods provide as good or better results to multiple-instance learning." at the IEEE International Conference on Computer Vision (ICCV), Santiago, Chile, 2015.

License

ragavvenkatesan/np-mil

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

5 Commits
 
 
 
 
 
 
 
 
 
 

Repository files navigation

This is the code for the paper

Ragav Venkatesan, Parag Shridhar Chandakkar, Baoxin Li "Simpler non-parametric methods provide as good or better results to multiple-instance learning." at the IEEE International Conference on Computer Vision (ICCV), Santiago, Chile, 2015.

The code also contains the DR dataset and one Synthetic datasets. To run the code, simply setup the parameters in MILLooper.m and run. The parameters are self-explanatory and are commented upon in a detailed manner in the code itself. The code only has the brute force optimization. Due to license issues I am not able to provide the EMDD version of the code, for which I used the original Y.Chen's executable. It is not difficult to implement from there on. The results are close but are not the same as reported because of the change in optimization methodology.

Thanks for using the code, hope you had fun.

Ragav Venkatesan http://www.public.asu.edu/~rvenka10

About

Code for Ragav Venkatesan, Parag Shridhar Chandakkar, Baoxin Li "Simpler non-parametric methods provide as good or better results to multiple-instance learning." at the IEEE International Conference on Computer Vision (ICCV), Santiago, Chile, 2015.

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published