mlsanityData to 7 Oct 2026

Concealed Object Detection

arXiv 2102.10274 ↗First posted 20 Feb 2021cs.CVcited by 212

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Abstract (arXiv)

We present the first systematic study on concealed object detection (COD), which aims to identify objects that are "perfectly" embedded in their background. The high intrinsic similarities between the concealed objects and their background make COD far more challenging than traditional object detection/segmentation. To better understand this task, we collect a large-scale dataset, called COD10K, which consists of 10,000 images covering concealed objects in diverse real-world scenarios from 78 object categories. Further, we provide rich annotations including object categories, object boundaries, challenging attributes, object-level labels, and instance-level annotations. Our COD10K is the largest COD dataset to date, with the richest annotations, which enables comprehensive concealed object understanding and can even be used to help progress several other vision tasks, such as detection, segmentation, classification, etc. Motivated by how animals hunt in the wild, we also design a simple but strong baseline for COD, termed the Search Identification Network (SINet). Without any bells and whistles, SINet outperforms 12 cutting-edge baselines on all datasets tested, making them robust, general architectures that could serve as catalysts for future research in COD. Finally, we provide some interesting findings and highlight several potential applications and future directions. To spark research in this new field, our code, dataset, and online demo are available on our project page: http://mmcheng.net/cod.

Key facts. Cited by 212 papers in the map (data through 7 Oct 2026). Builds on 65 of its 120 references that are in the map. First posted on arXiv 20 Feb 2021.

Builds on

65 of 120 references.

References · 65

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38 more
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  2. 2018Taskonomy: Disentangling Task Transfer Learningcited by 631
  3. 2018Object Detection with Deep Learning: A Reviewcited by 524
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  15. 2019Cascaded Partial Decoder for Fast and Accurate Salient Object Detectioncited by 216
  16. 2019A Simple Pooling-Based Design for Real-Time Salient Object Detectioncited by 211
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  23. 2019Salient Object Detection in the Deep Learning Era: An In-Depth Surveycited by 163
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50 most cited of 65 All 65 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 16; 2022: 20; 2023: 47; 2024: 52; 2025: 45; 2026: 32.

212 papers.

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  1. 2021Pyramid Vision Transformer: A Versatile Backbone for Dense Prediction without Convolutionscited by 1,960
  2. 2021Simultaneously Localize, Segment and Rank the Camouflaged Objectscited by 198
  3. 2021Polyp-PVT: Polyp Segmentation with Pyramid Vision Transformerscited by 159
  4. 2022Zoom In and Out: A Mixed-scale Triplet Network for Camouflaged Object Detectioncited by 145
  5. 2024VisionLLM v2: An End-to-End Generalist Multimodal Large Language Model for Hundreds of Vision-Language Taskscited by 136
  6. 2023Segment Anything Is Not Always Perfect: An Investigation of SAM on Different Real-world Applicationscited by 121
  7. 2022Towards Large-Scale Small Object Detection: Survey and Benchmarkscited by 119
  8. 2024Bilateral Reference for High-Resolution Dichotomous Image Segmentationcited by 112
  9. 2022Highly Accurate Dichotomous Image Segmentationcited by 110
  10. 2021Mutual Graph Learning for Camouflaged Object Detectioncited by 103
  11. 2023Can SAM Segment Anything? When SAM Meets Camouflaged Object Detectioncited by 99
  12. 2023Weakly-Supervised Concealed Object Segmentation with SAM-based Pseudo Labeling and Multi-scale Feature Groupingcited by 92
38 more
  1. 2023Feature Shrinkage Pyramid for Camouflaged Object Detection with Transformerscited by 87
  2. 2021Context-aware Cross-level Fusion Network for Camouflaged Object Detectioncited by 86
  3. 2021Class-agnostic Object Detection with Multi-modal Transformercited by 85
  4. 2022Video Polyp Segmentation: A Deep Learning Perspectivecited by 81
  5. 2021Full-Duplex Strategy for Video Object Segmentationcited by 78
  6. 2022High-resolution Iterative Feedback Network for Camouflaged Object Detectioncited by 78
  7. 2023SAM Struggles in Concealed Scenes -- Empirical Study on Segment Anythingcited by 75
  8. 2024What Matters When Repurposing Diffusion Models for General Dense Perception Tasks?cited by 74
  9. 2021Specificity-preserving RGB-D Saliency Detectioncited by 70
  10. 2023Reti-Diff: Illumination Degradation Image Restoration with Retinex-based Latent Diffusion Modelcited by 69
  11. 2022Boundary-Guided Camouflaged Object Detectioncited by 68
  12. 2024Convolution Meets LoRA: Parameter Efficient Finetuning for Segment Anything Modelcited by 67
  13. 2022Deep Gradient Learning for Efficient Camouflaged Object Detectioncited by 65
  14. 2022Implicit Motion Handling for Video Camouflaged Object Detectioncited by 60
  15. 2022CamoFormer: Masked Separable Attention for Camouflaged Object Detectioncited by 58
  16. 2023Strategic Preys Make Acute Predators: Enhancing Camouflaged Object Detectors by Generating Camouflaged Objectscited by 56
  17. 2022Source-free Depth for Object Pop-outcited by 52
  18. 2023ZoomNeXt: A Unified Collaborative Pyramid Network for Camouflaged Object Detectioncited by 48
  19. 2021CAVER: Cross-Modal View-Mixed Transformer for Bi-Modal Salient Object Detectioncited by 47
  20. 2023Advances in Deep Concealed Scene Understandingcited by 47
  21. 2024Frequency-Spatial Entanglement Learning for Camouflaged Object Detectioncited by 46
  22. 2022Weakly-Supervised Camouflaged Object Detection with Scribble Annotationscited by 43
  23. 2024Cross-Domain Few-Shot Object Detection via Enhanced Open-Set Object Detectorcited by 43
  24. 2021Fast Camouflaged Object Detection via Edge-based Reversible Re-calibration Networkcited by 42
  25. 2022Feature Aggregation and Propagation Network for Camouflaged Object Detectioncited by 40
  26. 2023Frequency Perception Network for Camouflaged Object Detectioncited by 37
  27. 2024A Survey of Camouflaged Object Detection and Beyondcited by 37
  28. 2021Depth Quality-Inspired Feature Manipulation for Efficient RGB-D Salient Object Detectioncited by 33
  29. 2022Camouflaged Object Detection via Context-aware Cross-level Fusioncited by 32
  30. 2024Effectiveness Assessment of Recent Large Vision-Language Modelscited by 29
  31. 2024Multi-Scale and Detail-Enhanced Segment Anything Model for Salient Object Detectioncited by 29
  32. 2025RUN: Reversible Unfolding Network for Concealed Object Segmentationcited by 28
  33. 2023Diffusion Model for Camouflaged Object Detectioncited by 27
  34. 2023TransNetR: Transformer-based Residual Network for Polyp Segmentation with Multi-Center Out-of-Distribution Testingcited by 26
  35. 2022Boosting Camouflaged Object Detection with Dual-Task Interactive Transformercited by 24
  36. 2023What a MESS: Multi-Domain Evaluation of Zero-Shot Semantic Segmentationcited by 24
  37. 2024A Simple yet Effective Network based on Vision Transformer for Camouflaged Object and Salient Object Detectioncited by 23
  38. 2024SAM-COD: SAM-guided Unified Framework for Weakly-Supervised Camouflaged Object Detectioncited by 22

50 most cited of 212 All 212 (JSON)