@inproceedings{baa5a9b5f9bd4a9bad66763da1759b9d,
title = "SFC: Shared Feature Calibration in Weakly Supervised Semantic Segmentation",
abstract = "Image-level weakly supervised semantic segmentation has received increasing attention due to its low annotation cost.Existing methods mainly rely on Class Activation Mapping (CAM) to obtain pseudo-labels for training semantic segmentation models.In this work, we are the first to demonstrate that long-tailed distribution in training data can cause the CAM calculated through classifier weights over-activated for head classes and under-activated for tail classes due to the shared features among head-and tail-classes.This degrades pseudo-label quality and further influences final semantic segmentation performance.To address this issue, we propose a Shared Feature Calibration (SFC) method for CAM generation.Specifically, we leverage the class prototypes that carry positive shared features and propose a Multi-Scaled Distribution-Weighted (MSDW) consistency loss for narrowing the gap between the CAMs generated through classifier weights and class prototypes during training.The MSDW loss counterbalances over-activation and under-activation by calibrating the shared features in head-/tail-class classifier weights.Experimental results show that our SFC significantly improves CAM boundaries and achieves new state-of-the-art performances.The project is available at https://github.com/Barrett-python/SFC.",
author = "Xinqiao Zhao and Feilong Tang and Xiaoyang Wang and Jimin Xiao",
note = "Publisher Copyright: Copyright {\textcopyright} 2024, Association for the Advancement of Artificial Intelligence (www.aaai.org).All rights reserved.; 38th AAAI Conference on Artificial Intelligence, AAAI 2024 ; Conference date: 20-02-2024 Through 27-02-2024",
year = "2024",
month = mar,
day = "25",
doi = "10.1609/aaai.v38i7.28584",
language = "English",
series = "Proceedings of the AAAI Conference on Artificial Intelligence",
publisher = "Association for the Advancement of Artificial Intelligence",
number = "7",
pages = "7525--7533",
editor = "Michael Wooldridge and Jennifer Dy and Sriraam Natarajan",
booktitle = "Technical Tracks 14",
edition = "7",
}