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Progressive Multi-scale Fusion Network for RGB-D Salient Object Detection

arXiv 2106.03941 ↗First posted 7 Jun 2021cs.CVcited by 0

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Abstract (arXiv)

Salient object detection(SOD) aims at locating the most significant object within a given image. In recent years, great progress has been made in applying SOD on many vision tasks. The depth map could provide additional spatial prior and boundary cues to boost the performance. Combining the depth information with image data obtained from standard visual cameras has been widely used in recent SOD works, however, introducing depth information in a suboptimal fusion strategy may have negative influence in the performance of SOD. In this paper, we discuss about the advantages of the so-called progressive multi-scale fusion method and propose a mask-guided feature aggregation module(MGFA). The proposed framework can effectively combine the two features of different modalities and, furthermore, alleviate the impact of erroneous depth features, which are inevitably caused by the variation of depth quality. We further introduce a mask-guided refinement module(MGRM) to complement the high-level semantic features and reduce the irrelevant features from multi-scale fusion, leading to an overall refinement of detection. Experiments on five challenging benchmarks demonstrate that the proposed method outperforms 11 state-of-the-art methods under different evaluation metrics.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 23 of its 47 references that are in the map. First posted on arXiv 7 Jun 2021.

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23 of 47 references.

References · 23

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11 more
  1. 2018Weakly-Supervised Semantic Segmentation by Iteratively Mining Common Object Featurescited by 81
  2. 2020RGB-D Salient Object Detection: A Surveycited by 73
  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. 2016RGBD Salient Object Detection via Deep Fusioncited by 46
  6. 2020Progressively Guided Alternate Refinement Network for RGB-D Salient Object Detectioncited by 40
  7. 2019Mask-Guided Attention Network for Occluded Pedestrian Detectioncited by 36
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  9. 2017Saliency Detection for Stereoscopic Images Based on Depth Confidence Analysis and Multiple Cues Fusioncited by 28
  10. 2020Single-Shot Two-Pronged Detector with Rectified IoU Losscited by 5
  11. 2020Salient Object Detection Combining a Self-attention Module and a Feature Pyramid Networkcited by 3

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