Class activation map guided level sets for weakly supervised semantic segmentation

Weakly supervised semantic segmentation (WSSS) aims to achieve pixel-level fine-grained image segmentation using only weak guidance such as image-level class labels, thus significantly decreasing annotation costs. Despite the impressive performance showcased by current state-of-the-art WSSS approach...

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Bibliographic Details
Main Authors: Yifan Wang, Gerald Schaefer, Xiyao Liu, Jing Dong, Linglin Jing, Ye Wei, Xianghua Xie, Hui Fang
Format: Default Article
Published: 2025
Subjects:
Engineering
Information and computing sciences
Computer vision and multimedia computation
Data management and data science
Information systems
Machine learning
Weakly supervised semantic segmentation
Class activation map
Pseudo-label
Level set
Fourier neural operator
Online Access:https://hdl.handle.net/2134/28554107.v1
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