Supplementary Material + TextonBoost code

If you're using any of the material or code on this page, cite our paper Efficient Inference in Fully Connected CRFs with Gaussian Edge Potentials .

TextonBoost code:
Here is an implementation of textonboost that should give you about 83-84% on MSRC. The code is provided as is, so please don't write me about getting it to run properly. I haven't tested it on any OS but linux. It's under BSD license. TextonBoost is probably patented. In any case it should be used for research only.

How to use:

This will create a bunch of binary files that can be loaded as "Image<float>". The values are either energies or probabilities depending on the RAW_BOOSTING_OUTPUT flag (on: energies, off: probabilities).

Additional material and dataset:
We split the MSRC training data in the following way. The accurate annotations can be found here.

To get textonboost to yield a decent result on VOC 2010 you need to train a bounding box classifier and use its response as a texton for texton boost. We used Discriminatively Trained Deformable Part Models.