SCALE-AWARE MULTI-LEVEL GUIDANCE FOR INTERACTIVE INSTANCE SEGMENTATION

作     者：Majumder, Soumajit Yao, Angela 

作者机构：Institute of Computer Science II University of Bonn School of Computing National University of Singapore 

出 版 物：《arXiv》 (arXiv)

年 卷 期：2018年

核心收录：

摘      要：In interactive instance segmentation, users give feedback to iteratively refine segmentation masks. The user-provided clicks are transformed into guidance maps which provide the network with necessary cues on the whereabouts of the object of interest. Guidance maps used in current systems are purely distance-based and are either too localized or non-informative. We propose a novel transformation of user clicks to generate scale-aware guidance maps that leverage the hierarchical structural information present in an image. Using our guidance maps, even the most basic FCNs are able to outperform existing approaches that require state-of-the-art segmentation networks pre-trained on large scale segmentation datasets. We demonstrate the effectiveness of our proposed transformation strategy through comprehensive experimentation in which we significantly raise state-of-the-art on four standard interactive segmentation benchmarks. Copyright © 2018, The Authors. All rights reserved.