Constrained-CNN losses for weakly supervised segmentation

12 May 2018Hoel KervadecJose DolzMeng TangEric GrangerYuri BoykovIsmail Ben Ayed

Weakly-supervised learning based on, e.g., partially labelled images or image-tags, is currently attracting significant attention in CNN segmentation as it can mitigate the need for full and laborious pixel/voxel annotations. Enforcing high-order (global) inequality constraints on the network output (for instance, to constrain the size of the target region) can leverage unlabeled data, guiding the training process with domain-specific knowledge... (read more)

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