mlsanityData to 7 Oct 2026

Fast Camouflaged Object Detection via Edge-based Reversible Re-calibration Network

arXiv 2111.03216 ↗First posted 5 Nov 2021cs.CVcited by 42

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Abstract (arXiv)

Camouflaged Object Detection (COD) aims to detect objects with similar patterns (e.g., texture, intensity, colour, etc) to their surroundings, and recently has attracted growing research interest. As camouflaged objects often present very ambiguous boundaries, how to determine object locations as well as their weak boundaries is challenging and also the key to this task. Inspired by the biological visual perception process when a human observer discovers camouflaged objects, this paper proposes a novel edge-based reversible re-calibration network called ERRNet. Our model is characterized by two innovative designs, namely Selective Edge Aggregation (SEA) and Reversible Re-calibration Unit (RRU), which aim to model the visual perception behaviour and achieve effective edge prior and cross-comparison between potential camouflaged regions and background. More importantly, RRU incorporates diverse priors with more comprehensive information comparing to existing COD models. Experimental results show that ERRNet outperforms existing cutting-edge baselines on three COD datasets and five medical image segmentation datasets. Especially, compared with the existing top-1 model SINet, ERRNet significantly improves the performance by ~6% (mean E-measure) with notably high speed (79.3 FPS), showing that ERRNet could be a general and robust solution for the COD task.

Key facts. Cited by 42 papers in the map (data through 7 Oct 2026). Builds on 48 of its 94 references that are in the map. First posted on arXiv 5 Nov 2021.

Builds on

48 of 94 references.

References · 48

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 9; 2023: 14; 2024: 12; 2025: 6; 2026: 1.

42 papers.

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  1. 2023Can SAM Segment Anything? When SAM Meets Camouflaged Object Detectioncited by 99
  2. 2022Video Polyp Segmentation: A Deep Learning Perspectivecited by 81
  3. 2022Deep Gradient Learning for Efficient Camouflaged Object Detectioncited by 65
  4. 2022CamoFormer: Masked Separable Attention for Camouflaged Object Detectioncited by 58
  5. 2023Advances in Deep Concealed Scene Understandingcited by 47
  6. 2022Feature Aggregation and Propagation Network for Camouflaged Object Detectioncited by 40
  7. 2024A Survey of Camouflaged Object Detection and Beyondcited by 37
  8. 2022Camouflaged Object Detection via Context-aware Cross-level Fusioncited by 32
  9. 2024Effectiveness Assessment of Recent Large Vision-Language Modelscited by 29
  10. 2023Diffusion Model for Camouflaged Object Detectioncited by 27
  11. 2022Boosting Camouflaged Object Detection with Dual-Task Interactive Transformercited by 24
  12. 2022DuAT: Dual-Aggregation Transformer Network for Medical Image Segmentationcited by 22
30 more
  1. 2023Chain of Visual Perception: Harnessing Multimodal Large Language Models for Zero-shot Camouflaged Object Detectioncited by 22
  2. 2022Towards Deeper Understanding of Camouflaged Object Detectioncited by 19
  3. 2023Referring Camouflaged Object Detectioncited by 19
  4. 2023Towards Diverse Binary Segmentation via A Simple yet General Gated Networkcited by 17
  5. 2024Frequency-Guided Spatial Adaptation for Camouflaged Object Detectioncited by 15
  6. 2025Integrating Extra Modality Helps Segmentor Find Camouflaged Objects Wellcited by 14
  7. 2024Evaluating SAM2's Role in Camouflaged Object Detection: From SAM to SAM2cited by 12
  8. 2024GLCONet: Learning Multi-source Perception Representation for Camouflaged Object Detectioncited by 10
  9. 2023Collaborative Camouflaged Object Detection: A Large-Scale Dataset and Benchmarkcited by 8
  10. 2023Large Model Based Referring Camouflaged Object Detectioncited by 8
  11. 2023PrObeD: Proactive Object Detection Wrappercited by 7
  12. 2024COMPrompter: reconceptualized segment anything model with multiprompt network for camouflaged object detectioncited by 6
  13. 2025Deep Learning in Concealed Dense Predictioncited by 6
  14. 2024PlantCamo: Plant Camouflage Detectioncited by 5
  15. 2023Pre-train, Adapt and Detect: Multi-Task Adapter Tuning for Camouflaged Object Detectioncited by 4
  16. 2024Adaptive Guidance Learning for Camouflaged Object Detectioncited by 4
  17. 2023Joint Salient Object Detection and Camouflaged Object Detection via Uncertainty-aware Learningcited by 3
  18. 2023You Do Not Need Additional Priors in Camouflage Object Detectioncited by 2
  19. 2023Cross-level Attention with Overlapped Windows for Camouflaged Object Detectioncited by 2
  20. 2025Synthetic-to-Real Camouflaged Object Detectioncited by 2
  21. 2022Boundary-aware Camouflaged Object Detection via Deformable Point Samplingcited by 1
  22. 2023A bioinspired three-stage model for camouflaged object detectioncited by 0
  23. 2024Shifting Spotlight for Co-supervision: A Simple yet Efficient Single-branch Network to See Through Camouflagecited by 0
  24. 2024Patch is Enough: Naturalistic Adversarial Patch against Vision-Language Pre-training Modelscited by 0
  25. 2024SurANet: Surrounding-Aware Network for Concealed Object Detection via Highly-Efficient Interactive Contrastive Learning Strategycited by 0
  26. 2024Defective Edge Detection Using Cascaded Ensemble Canny Operatorcited by 0
  27. 2025First RAG, Second SEG: A Training-Free Paradigm for Camouflaged Object Detectioncited by 0
  28. 2025JVLGS: Joint Vision-Language Gas Leak Segmentationcited by 0
  29. 2025RefOnce: Distilling References into a Prototype Memory for Referring Camouflaged Object Detectioncited by 0
  30. 2026Uncertainty Estimation in Instance Segmentation of Affordances via Bayesian Visual Transformerscited by 0