@misc{brust2015efficient,
    type = {misc},
    key = {brust2015efficient},
    title = {Efficient Convolutional Patch Networks for Scene Understanding},
    author = {Clemens-Alexander Brust and Sven Sickert and Marcel Simon and Erik Rodner and Joachim Denzler},
    note = {Poster presentation and extended abstract},
    year = {2015},
    abstract = {In this paper, we present convolutional patch networks, which are convolutional (neural) networks (CNN) learned to distinguish different image patches and which can be used for pixel-wise labeling. We show how to easily learn spatial priors for certain categories jointly with their appearance. Experiments for urban scene understanding demonstrate state-of-the-art results on the LabelMeFacade dataset. Our approach is implemented as a new CNN framework especially designed for semantic segmentation with fully-convolutional architectures.},
    howpublished = {CVPR Workshop on Scene Understanding (CVPR-WS)},
    groups = {semanticsegmentation,deeplearning,urbansceneunderstanding},
}