A MATLAB wrapper for solving DenseCRF problems [1,2]. The code uses the c++ library provided with [2].
-
Solving a general problem see examples/example.m.
-
Segmentation on the MSRC-21 database using the unary potentials from http://graphics.stanford.edu/projects/densecrf/unary/ see examples/example_MSRC.m
- Mean field approximation, using approximate filtering [2].
- Mean field approximation, performing all summations explicitly (slow).
- TRWS-S [3].
- Graph cuts for 2 label problems [4].
-
Efficient Inference in Fully Connected CRFs with Gaussian Edge Potentials.
Conference on Neural Information Processing Systems (NIPS), 2011.
Philipp Krähenbühl and Vladlen Koltun. -
Parameter Learning and Convergent Inference for Dense Random Fields.
International Conference on Machine Learning (ICML), 2013.
Philipp Krähenbühl and Vladlen Koltun. -
Convergent Tree-reweighted Message Passing for Energy Minimization.
IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2006.
Vladimir Kolmogorov. -
An Experimental Comparison of Min-Cut/Max-Flow Algorithms for Energy Minimization in Computer Vision.
IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2004