CRF learning with CNN features for image segmentation
A deep CNN pretrained on ImageNet generalizes well to various segmentation datasets. Deep features significantly outperform BoW and unsupervisd feature learning. Combining deep CNN features with CRF yields new state-of-the-art results. Incorporating spatial related co-occurrence potentials further improves the accuracy.
co-occurrence conditional random field (crf) convolutional neural network (cnn) structured support vector machine (ssvm)