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2021 | OriginalPaper | Chapter

Assessing the Role of Boundary-Level Objectives in Indoor Semantic Segmentation

Authors : Roberto Amoroso, Lorenzo Baraldi, Rita Cucchiara

Published in: Computer Analysis of Images and Patterns

Publisher: Springer International Publishing

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Abstract

The chapter delves into the critical task of indoor scene understanding through semantic segmentation, highlighting the challenges posed by the lack of depth information in RGB images. It introduces the concept of boundary-level objectives, specifically focusing on Boundary loss and Active Boundary loss, to address the issue of blurred object boundaries in semantic segmentation. The authors propose and evaluate novel variations of these loss functions, demonstrating their effectiveness in improving segmentation accuracy. Experimental results on the NYUDv2 dataset showcase the potential of these approaches in enhancing the performance of semantic segmentation models in indoor environments.
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Metadata
Title
Assessing the Role of Boundary-Level Objectives in Indoor Semantic Segmentation
Authors
Roberto Amoroso
Lorenzo Baraldi
Rita Cucchiara
Copyright Year
2021
Book
Computer Analysis of Images and Patterns

Print ISBN: 978-3-030-89127-5

Electronic ISBN: 978-3-030-89128-2

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-3-030-89128-2_44

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