Efficient and Robust Deep Networks for Semantic Segmentation

Abstract

This paper explores and investigates Deep Convolutional Neural Networks (DCNNs) architectures to increase efficiency and robustness of semantic segmentation tasks. The proposed solutions are based on Up-Convolutional Networks. We introduce three different architectures in this work. The first architecture, called Part-Net, is designed to tackle the specific… (More)

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Cite this paper

@inproceedings{Oliveira2017EfficientAR, title={Efficient and Robust Deep Networks for Semantic Segmentation}, author={Gabriel L. Oliveira and Claas Bollen and Wolfram Burgard and Thomas Brox}, year={2017} }