research-article

Dual-aware Domain Mining and Cross-aware Supervision for Weakly-supervised Semantic Segmentation

Authors:

Xiangping Zheng,

Xuan ZhangAuthors Info & Claims

ACM Transactions on Knowledge Discovery from Data, Volume 17, Issue 7

Article No.: 101, Pages 1 - 19

https://doi.org/10.1145/3589343

Published: 04 May 2023 Publication History

Abstract

Weakly Supervised Semantic Segmentation with image-level annotation uses localization maps from the classifier to generate pseudo labels. However, such localization maps focus only on sparse salient object regions, it is difficult to generate high-quality segmentation labels, which deviates from the requirement of semantic segmentation. To address this issue, we propose a dual-aware domain mining and cross-aware supervision (DDMCAS) method for weakly-supervised semantic segmentation. Specifically, we propose a dual-aware domain mining (DDM) module consisting of graph-based global reasoning unit and salient-region extension controller, which produces dense localization maps by exploring object features in salient regions and adjacent non-salient regions simultaneously. In order to further bridge the gap between salient regions and adjacent non-salient regions to generate more refined localization maps, we propose a cross-aware supervision (CAS) strategy to recover missing parts of the target objects and enhance weak attention in adjacent non-salient regions, leading to pseudo labels of higher quality for training the segmentation network. Based on the generated pseudo-labels, extensive experiments on PASCAL VOC 2012 dataset demonstrate that our method outperforms state-of-the-art methods using image-level labels for weakly supervised semantic segmentation.

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Cited By

Pandey SPatel A(2025)Urban scene representation and summarization using knowledge graphExpert Systems with Applications10.1016/j.eswa.2025.126956275(126956)Online publication date: May-2025
https://doi.org/10.1016/j.eswa.2025.126956
Liu MLi WGe FGao X(2024)Weakly-supervised temporal action localization using multi-branch attention weightingMultimedia Systems10.1007/s00530-024-01445-230:5Online publication date: 30-Aug-2024
https://dl.acm.org/doi/10.1007/s00530-024-01445-2

Index Terms

Dual-aware Domain Mining and Cross-aware Supervision for Weakly-supervised Semantic Segmentation
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
        Image segmentation
      2. Computer vision tasks
        Scene understanding

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cover image ACM Transactions on Knowledge Discovery from Data

ACM Transactions on Knowledge Discovery from Data Volume 17, Issue 7

August 2023

319 pages

ISSN:1556-4681

EISSN:1556-472X

DOI:10.1145/3589018

Editor:
Charu Aggarwal
IBM T. J. Watson Research, USA

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Publication History

Published: 04 May 2023

Online AM: 25 March 2023

Accepted: 21 March 2023

Revised: 03 January 2023

Received: 08 November 2021

Published in TKDD Volume 17, Issue 7

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National Natural Science Foundation of China
National Social Science Foundation of China
Research Seed Funds of School of Interdisciplinary Studies of Renmin University of China
Opening Project of State Key Laboratory of Digital Publishing Technology of Founder Group

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Cited By

Pandey SPatel A(2025)Urban scene representation and summarization using knowledge graphExpert Systems with Applications10.1016/j.eswa.2025.126956275(126956)Online publication date: May-2025
https://doi.org/10.1016/j.eswa.2025.126956
Liu MLi WGe FGao X(2024)Weakly-supervised temporal action localization using multi-branch attention weightingMultimedia Systems10.1007/s00530-024-01445-230:5Online publication date: 30-Aug-2024
https://dl.acm.org/doi/10.1007/s00530-024-01445-2

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