Fully Convolutional Multi-Class Multiple Instance Learning

International Conference on Learning Representations, 2014.

Cited by: 148|Bibtex|Views220
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Other Links: dblp.uni-trier.de|academic.microsoft.com|arxiv.org

Abstract:

Multiple instance learning (MIL) can reduce the need for costly annotation in tasks such as semantic segmentation by weakening the required degree of supervision. We propose a novel MIL formulation of multi-class semantic segmentation learning by a fully convolutional network. In this setting, we seek to learn a semantic segmentation mo...More

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