mlsanityData to 14 Oct 2026

When Super-Resolution Meets Camouflaged Object Detection: A Comparison Study

arXiv 2308.04370 ↗First posted 8 Aug 2023cs.CVcited by 1

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Abstract (arXiv)

Super Resolution (SR) and Camouflaged Object Detection (COD) are two hot topics in computer vision with various joint applications. For instance, low-resolution surveillance images can be successively processed by super-resolution techniques and camouflaged object detection. However, in previous work, these two areas are always studied in isolation. In this paper, we, for the first time, conduct an integrated comparative evaluation for both. Specifically, we benchmark different super-resolution methods on commonly used COD datasets, and meanwhile, we evaluate the robustness of different COD models by using COD data processed by SR methods. Our goal is to bridge these two domains, discover novel experimental phenomena, summarize new experim.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 25 of its 43 references that are in the map. First posted on arXiv 8 Aug 2023.

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25 of 43 references.

References · 25

  1. 2021Swin Transformer: Hierarchical Vision Transformer using Shifted Windowscited by 12,139
  2. 2019EfficientNet: Rethinking Model Scaling for Convolutional Neural Networkscited by 6,442
  3. 2016Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Networkcited by 1,908
  4. 2021SwinIR: Image Restoration Using Swin Transformercited by 1,887
  5. 2017Enhanced Deep Residual Networks for Single Image Super-Resolutioncited by 1,552
  6. 2018ESRGAN: Enhanced Super-Resolution Generative Adversarial Networkscited by 1,254
  7. 2017Structure-measure: A New Way to Evaluate Foreground Mapscited by 480
  8. 2020Plug-and-Play Image Restoration with Deep Denoiser Priorcited by 470
  9. 2015Sketch-based Manga Retrieval using Manga109 Datasetcited by 329
  10. 2021Anabranch Network for Camouflaged Object Segmentationcited by 227
  11. 2021Concealed Object Detectioncited by 212
  12. 2021Simultaneously Localize, Segment and Rank the Camouflaged Objectscited by 198
13 more
  1. 2021Camouflaged Object Segmentation with Distraction Miningcited by 151
  2. 2021Mutual Graph Learning for Camouflaged Object Detectioncited by 103
  3. 2020UC-Net: Uncertainty Inspired RGB-D Saliency Detection via Conditional Variational Autoencoderscited by 98
  4. 2022Cross Aggregation Transformer for Image Restorationcited by 92
  5. 2021Context-aware Cross-level Fusion Network for Camouflaged Object Detectioncited by 86
  6. 2022Accurate Image Restoration with Attention Retractable Transformercited by 85
  7. 2022Boundary-Guided Camouflaged Object Detectioncited by 68
  8. 2022Deep Gradient Learning for Efficient Camouflaged Object Detectioncited by 65
  9. 2022CamoFormer: Masked Separable Attention for Camouflaged Object Detectioncited by 58
  10. 2022Feature Aggregation and Propagation Network for Camouflaged Object Detectioncited by 40
  11. 2022Camouflaged Object Detection via Context-aware Cross-level Fusioncited by 32
  12. 2021Improving Camouflaged Object Detection with the Uncertainty of Pseudo-edge Labelscited by 16
  13. 2020Camouflaged Object Detection and Tracking: A Surveycited by 14

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  1. 2025MatIR: A Hybrid Mamba-Transformer Image Restoration Modelcited by 2