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2017 | OriginalPaper | Chapter

Instance Semantic Segmentation via Scale-Aware Patch Fusion Network

Authors : Jinfu Yang, Jingling Zhang, Mingai Li, Meijie Wang

Published in: Computer Vision

Publisher: Springer Singapore

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Abstract

Instance semantic segmentation has already been a promising direction, but many leading approaches are lack of detailed structural information and unable to segment small size objects. In this paper, we present a novel segmentation framework, called Scale-aware Patch Fusion Network (SPF). Our unified end-to-end trainable network consists of three components, namely, multi-scale patch generator, semantic segmentation network and patch fusion algorithm. This patch-based method aggregates information from different scales of patches via fusing local segmentation prediction results. The proposed approach is thus more effective and simple. Experiments on VOC 2012 segmentation val, VOC 2012 SDS val, MS COCO datasets validate the effectiveness of our approach.

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Title: Instance Semantic Segmentation via Scale-Aware Patch Fusion Network
Authors: Jinfu Yang
Jingling Zhang
Mingai Li
Meijie Wang
Publisher: Springer Singapore
Book: Computer Vision
Print ISBN: 978-981-10-7301-4

Electronic ISBN: 978-981-10-7302-1

Copyright Year: 2017
DOI: https://doi.org/10.1007/978-981-10-7302-1_43

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