mlsanityData to 14 Oct 2026

FIPGNet:Pyramid grafting network with feature interaction strategies

arXiv 2407.04085 ↗First posted 4 Jul 2024cs.CVcited by 0

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Abstract (arXiv)

Salient object detection is designed to identify the objects in an image that attract the most visual attention.Currently, the most advanced method of significance object detection adopts pyramid grafting network architecture.However, pyramid-graft network architecture still has the problem of failing to accurately locate significant targets.We observe that this is mainly due to the fact that current salient object detection methods simply aggregate different scale features, ignoring the correlation between different scale features.To overcome these problems, we propose a new salience object detection framework(FIPGNet),which is a pyramid graft network with feature interaction strategies.Specifically, we propose an attention-mechanism based feature interaction strategy (FIA) that innovatively introduces spatial agent Cross Attention (SACA) to achieve multi-level feature interaction, highlighting important spatial regions from a spatial perspective, thereby enhancing salient regions.And the channel proxy Cross Attention Module (CCM), which is used to effectively connect the features extracted by the backbone network and the features processed using the spatial proxy cross attention module, eliminating inconsistencies.Finally, under the action of these two modules, the prominent target location problem in the current pyramid grafting network model is solved.Experimental results on six challenging datasets show that the proposed method outperforms the current 12 salient object detection methods on four indicators.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 23 of its 39 references that are in the map. First posted on arXiv 4 Jul 2024.

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23 of 39 references.

References · 23

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11 more
  1. 2021Salient Object Detection via Integrity Learningcited by 133
  2. 2020Suppress and Balance: A Simple Gated Network for Salient Object Detectioncited by 126
  3. 2022Pyramid Grafting Network for One-Stage High Resolution Saliency Detectioncited by 63
  4. 2021Disentangled High Quality Salient Object Detectioncited by 35
  5. 2018PiCANet: Pixel-wise Contextual Attention Learning for Accurate Saliency Detectioncited by 28
  6. 2023HRTransNet: HRFormer-Driven Two-Modality Salient Object Detectioncited by 27
  7. 2024Robust Semi-supervised Learning by Wisely Leveraging Open-set Datacited by 20
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  10. 2023Narrowing the semantic gaps in U-Net with learnable skip connections: The case of medical image segmentationcited by 9
  11. 2023M3Net: Multilevel, Mixed and Multistage Attention Network for Salient Object Detectioncited by 4

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