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arXiv · 1803.05200

Combining Multi-level Contexts of Superpixel using Convolutional Neural Networks to perform Natural Scene Labeling

Aritra Das·Swarnendu Ghosh·Ritesh Sarkhel·Sandipan Choudhuri·Nibaran Das·Mita Nasipuri
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Abstract

Modern deep learning algorithms have triggered various image segmentation approaches. However most of them deal with pixel based segmentation. However, superpixels provide a certain degree of contextual information while reducing computation cost. In our approach, we have performed superpixel level semantic segmentation considering 3 various levels as neighbours for semantic contexts. Furthermore, we have enlisted a number of ensemble approaches like max-voting and weighted-average. We have also used the Dempster-Shafer theory of uncertainty to analyze confusion among various classes. Our method has proved to be superior to a number of different modern approaches on the same dataset.

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Aritra Das, Swarnendu Ghosh, Ritesh Sarkhel, Sandipan Choudhuri, Nibaran Das, Mita Nasipuri. 2018-03-14. Combining Multi-level Contexts of Superpixel using Convolutional Neural Networks to perform Natural Scene Labeling. https://arxiv.org/abs/1803.05200

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