Effective semantic pixel labelling with convolutional networks and Conditional Random Fields

@article{Paisitkriangkrai2015EffectiveSP,
  title={Effective semantic pixel labelling with convolutional networks and Conditional Random Fields},
  author={Sakrapee Paisitkriangkrai and Jamie Sherrah and Pranam Janney and Anton van den Hengel},
  journal={2015 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)},
  year={2015},
  pages={36-43}
}
Large amounts of available training data and increasing computing power have led to the recent success of deep convolutional neural networks (CNN) on a large number of applications. In this paper, we propose an effective semantic pixel labelling using CNN features, hand-crafted features and Conditional Random Fields (CRFs). Both CNN and hand-crafted features are applied to dense image patches to produce per-pixel class probabilities. The CRF infers a labelling that smooths regions while… CONTINUE READING
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