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Dynamic Message Propagation Network for RGB-D and Video Salient Object Detection

Published: 18 September 2023 Publication History

Abstract

Exploiting long-range semantic contexts and geometric information is crucial to infer salient objects from RGB and depth features. However, existing methods mainly focus on excavating local features within fixed regions by continuously feeding forward networks. In this article, we introduce Dynamic Message Propagation (DMP) to dynamically learn context information within more flexible regions. We integrate DMP into a Siamese-based network to process the RGB image and depth map separately and design a multi-level feature fusion module to explore cross-level information between refined RGB and depth features. Extensive experiments show clear improvements of our method over 17 methods on six benchmark datasets for RGB-D salient object detection (SOD). Additionally, our method outperforms its competitors for the video SOD task. Code is available at https://github.com/chenbaian-cs/DMPNet.

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  1. Dynamic Message Propagation Network for RGB-D and Video Salient Object Detection

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    Published In

    cover image ACM Transactions on Multimedia Computing, Communications, and Applications
    ACM Transactions on Multimedia Computing, Communications, and Applications  Volume 20, Issue 1
    January 2024
    639 pages
    EISSN:1551-6865
    DOI:10.1145/3613542
    • Editor:
    • Abdulmotaleb El Saddik
    Issue’s Table of Contents

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 18 September 2023
    Online AM: 19 May 2023
    Accepted: 09 May 2023
    Revised: 28 April 2023
    Received: 08 December 2022
    Published in TOMM Volume 20, Issue 1

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    Author Tags

    1. RGB-D salient object detection
    2. dynamic message propagation
    3. cross-modal learning
    4. depth feature propagation

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    • Research-article

    Funding Sources

    • Shenzhen Science and Technology Program
    • General Program of Natural Science Foundation of Guangdong Province
    • Free Exploration of Basic Research Project, Local Science and Technology Development Fund Guided by the Central Government of China
    • Research Grant entitled “Self-Supervised Learning for Medical Images”’
    • Shenzhen University-Lingnan University Joint Research Programme

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    • (2024)Gated Multi-Modal Edge Refinement Network for Light Field Salient Object DetectionACM Transactions on Multimedia Computing, Communications, and Applications10.1145/367483620:10(1-20)Online publication date: 28-Jun-2024
    • (2024)Heterogeneous Fusion and Integrity Learning Network for RGB-D Salient Object DetectionACM Transactions on Multimedia Computing, Communications, and Applications10.1145/365647620:7(1-24)Online publication date: 15-May-2024
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