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Status: Unchecked ×Keyword: instance segmentation ×Clear all

3 claims from 1 paper

1. Computer Science › Advanced Neural Network Applications

   Path Aggregation Network for Instance Segmentation

   Liu, Qi, Qin, Shi and Jia · arXiv (Cornell University) · 2018

   The paper proposes PANet, which improves information flow in proposal-based instance segmentation and reports first place in the COCO 2017 instance segmentation challenge.

   Unchecked3 claims
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   1. UncheckedA bottom-up path added to the feature hierarchy carries precise localisation signals from lower layers upward, shortening the route to the topmost feature.“Specifically, we enhance the entire feature hierarchy with accurate localization signals in lower layers by bottom-up path augmentation, which shortens the information path between lower layers and topmost feature.”
   2. Unchecked“We present adaptive feature pooling, which links feature grid and all feature levels to make useful information in each feature level propagate directly to following proposal subnetworks.”
   3. UncheckedAdding a complementary branch that gives each object proposal a different view is said to further improve the mask prediction in instance segmentation.“A complementary branch capturing different views for each proposal is created to further improve mask prediction.”