Unsupervised learning of high-order structural semantics from images

@article{Gao2009UnsupervisedLO,
  title={Unsupervised learning of high-order structural semantics from images},
  author={Jizhou Gao and Yin Hu and Jinze Liu and Ruigang Yang},
  journal={2009 IEEE 12th International Conference on Computer Vision},
  year={2009},
  pages={2122-2129}
}
Structural semantics are fundamental to understanding both natural and man-made objects from languages to buildings. They are manifested as repeated structures or patterns and are often captured in images. Finding repeated patterns in images, therefore, has important applications in scene understanding, 3D reconstruction, and image retrieval as well as image compression. Previous approaches in visual-pattern mining limited themselves by looking for frequently co-occurring features within a… CONTINUE READING
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