Bottom-up top-down cues for weakly-supervised semantic segmentation
We consider the task of learning a classifier for semantic segmentation using weak supervision in the form of image labels specifying objects present in the image. Our method uses deep convolutional neural networks (cnns) and adopts an Expectation-Maximization (EM) based approach. We focus on the fo...
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| Médium: | Conference item |
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Springer, Cham
2018
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