Looking Beyond Single Images for Weakly Supervised Semantic Segmentation Learning

This article studies the problem of learning weakly supervised semantic segmentation (WSSS) from image-level supervision only. Current popular solutions leverage object localization maps from classifiers as supervision for semantic segmentation learning, and struggle to make the localization maps ca...

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Veröffentlicht in:	IEEE transactions on pattern analysis and machine intelligence Jg. 46; H. 3; S. 1635 - 1649
Hauptverfasser:	Wang, Wenguan, Sun, Guolei, Van Gool, Luc
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.03.2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Birds Classifiers co-attention cross-image semantic relation Data mining Image segmentation Localization Location awareness Machine learning Noise measurement Pattern analysis Semantic segmentation Semantics Supervision Training Training data weakly supervised learning
ISSN:	0162-8828, 1939-3539, 2160-9292, 1939-3539
Online-Zugang:	Volltext
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