mlsanityData to 7 Oct 2026

M2RNet: Multi-modal and Multi-scale Refined Network for RGB-D Salient Object Detection

arXiv 2109.07922 ↗First posted 16 Sep 2021cs.CVcited by 2

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Abstract (arXiv)

Salient object detection is a fundamental topic in computer vision. Previous methods based on RGB-D often suffer from the incompatibility of multi-modal feature fusion and the insufficiency of multi-scale feature aggregation. To tackle these two dilemmas, we propose a novel multi-modal and multi-scale refined network (M2RNet). Three essential components are presented in this network. The nested dual attention module (NDAM) explicitly exploits the combined features of RGB and depth flows. The adjacent interactive aggregation module (AIAM) gradually integrates the neighbor features of high, middle and low levels. The joint hybrid optimization loss (JHOL) makes the predictions have a prominent outline. Extensive experiments demonstrate that our method outperforms other state-of-the-art approaches.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 20 of its 46 references that are in the map. First posted on arXiv 16 Sep 2021.

Builds on

20 of 46 references.

References · 20

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
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8 more
  1. 2020UC-Net: Uncertainty Inspired RGB-D Saliency Detection via Conditional Variational Autoencoderscited by 98
  2. 2020JL-DCF: Joint Learning and Densely-Cooperative Fusion Framework for RGB-D Salient Object Detectioncited by 79
  3. 2020Hierarchical Dynamic Filtering Network for RGB-D Salient Object Detectioncited by 72
  4. 2020A Single Stream Network for Robust and Real-time RGB-D Salient Object Detectioncited by 67
  5. 2018Selectivity or Invariance: Boundary-aware Salient Object Detectioncited by 48
  6. 2020Cross-Modal Weighting Network for RGB-D Salient Object Detectioncited by 47
  7. 2016RGBD Salient Object Detection via Deep Fusioncited by 46
  8. 2019Adaptive Fusion for RGB-D Salient Object Detectioncited by 29

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Citing papers per year: 2025: 2.

2 papers.

  1. 2025Dual Mutual Learning Network with Global-local Awareness for RGB-D Salient Object Detectioncited by 0
  2. 2025Real-World Depth Recovery via Structure Uncertainty Modeling and Inaccurate GT Depth Fittingcited by 0