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Status: Unchecked ×Keyword: top-down refinement ×Clear all

2 claims from 1 paper

1. Computer Science › Advanced Neural Network Applications

   Learning to Refine Object Segments

   Pinheiro, Lin, Collobert and Dollár · arXiv (Cornell University) · 2016

   The paper adds a top-down refinement step to feedforward networks for object segmentation, giving sharper object masks and better accuracy than DeepMask, while also running faster.

   Unchecked2 claims
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   1. UncheckedBy optimising the overall network design, SharpMask runs about 50% faster than the original DeepMask network, at under 0.8 seconds per image.“Additionally, by optimizing the overall network architecture, our approach, which we call SharpMask, is 50% faster than the original DeepMask network (under .8s per image).”
   2. UncheckedAdding a top-down refinement step to the DeepMask object proposal network raised average recall by 10-20% across various setups, as the paper reports.“Building on the recent DeepMask network for generating object proposals, we show accuracy improvements of 10-20% in average recall for various setups.”