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A Revisit to the Decoder for Camouflaged Object Detection

arXiv 2503.14035 ↗First posted 18 Mar 2025cs.CVcited by 0

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Abstract (arXiv)

Camouflaged object detection (COD) aims to generate a fine-grained segmentation map of camouflaged objects hidden in their background. Due to the hidden nature of camouflaged objects, it is essential for the decoder to be tailored to effectively extract proper features of camouflaged objects and extra-carefully generate their complex boundaries. In this paper, we propose a novel architecture that augments the prevalent decoding strategy in COD with Enrich Decoder and Retouch Decoder, which help to generate a fine-grained segmentation map. Specifically, the Enrich Decoder amplifies the channels of features that are important for COD using channel-wise attention. Retouch Decoder further refines the segmentation maps by spatially attending to important pixels, such as the boundary regions. With extensive experiments, we demonstrate that ENTO shows superior performance using various encoders, with the two novel components playing their unique roles that are mutually complementary.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 21 of its 38 references that are in the map. First posted on arXiv 18 Mar 2025.

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21 of 38 references.

References · 21

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  12. 2021Camouflaged Object Segmentation with Distraction Miningcited by 151
9 more
  1. 2022Zoom In and Out: A Mixed-scale Triplet Network for Camouflaged Object Detectioncited by 145
  2. 2021Uncertainty-aware Joint Salient Object and Camouflaged Object Detectioncited by 114
  3. 2021Mutual Graph Learning for Camouflaged Object Detectioncited by 103
  4. 2019Towards High-Resolution Salient Object Detectioncited by 92
  5. 2023Feature Shrinkage Pyramid for Camouflaged Object Detection with Transformerscited by 87
  6. 2021Context-aware Cross-level Fusion Network for Camouflaged Object Detectioncited by 86
  7. 2022High-resolution Iterative Feedback Network for Camouflaged Object Detectioncited by 78
  8. 2022Boosting Camouflaged Object Detection with Dual-Task Interactive Transformercited by 24
  9. 2024Finding NeMo: Negative-mined Mosaic Augmentation for Referring Image Segmentationcited by 7

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