Segmentation system marks unknown objects which are then incrementally learned
Segmentation system marks unknown objects which are then incrementally learned
Deep Metric Learning for Open World Semantic Segmentation
arXiv paper abstract https://arxiv.org/abs/2108.04562v1
arXiv PDF paper https://arxiv.org/pdf/2108.04562v1.pdf
Classical … segmentation networks have limited ability to detect out-of-distribution (OOD) objects, which is important for safety-critical applications such as autonomous driving.
… propose … includes two modules:
(1) … detect both in-distribution and OOD objects.
(2) an incremental few-shot learning module to gradually incorporate those OOD objects into its existing knowledge base.
… system behaves like a human being, which is able to identify OOD objects and gradually learn them with corresponding supervision.
… DMLNet achieves state-of-the-art performance on three challenging open-set semantic segmentation datasets without using additional data or generative models. …
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