mlsanityData to 14 Oct 2026

Progressively Normalized Self-Attention Network for Video Polyp Segmentation

arXiv 2105.08468 ↗First posted 18 May 2021cs.CVcited by 75

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Abstract (arXiv)

Existing video polyp segmentation (VPS) models typically employ convolutional neural networks (CNNs) to extract features. However, due to their limited receptive fields, CNNs can not fully exploit the global temporal and spatial information in successive video frames, resulting in false-positive segmentation results. In this paper, we propose the novel PNS-Net (Progressively Normalized Self-attention Network), which can efficiently learn representations from polyp videos with real-time speed (~140fps) on a single RTX 2080 GPU and no post-processing. Our PNS-Net is based solely on a basic normalized self-attention block, equipping with recurrence and CNNs entirely. Experiments on challenging VPS datasets demonstrate that the proposed PNS-Net achieves state-of-the-art performance. We also conduct extensive experiments to study the effectiveness of the channel split, soft-attention, and progressive learning strategy. We find that our PNS-Net works well under different settings, making it a promising solution to the VPS task.

Key facts. Cited by 75 papers in the map (data through 14 Oct 2026). Builds on 16 of its 30 references that are in the map. First posted on arXiv 18 May 2021.

Builds on

16 of 30 references.

References · 16

  1. 2017Attention Is All You Needcited by 60,361
  2. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,713
  3. 2016Layer Normalizationcited by 5,669
  4. 2017Non-local Neural Networkscited by 2,293
  5. 2018UNet++: A Nested U-Net Architecture for Medical Image Segmentationcited by 1,525
  6. 2019Kvasir-SEG: A Segmented Polyp Datasetcited by 589
  7. 2017Structure-measure: A New Way to Evaluate Foreground Mapscited by 480
  8. 2020PraNet: Parallel Reverse Attention Network for Polyp Segmentationcited by 460
  9. 2018Enhanced-alignment Measure for Binary Foreground Map Evaluationcited by 370
  10. 2020Learning Texture Transformer Network for Image Super-Resolutioncited by 347
  11. 2019ResUNet++: An Advanced Architecture for Medical Image Segmentationcited by 211
  12. 2017Receptive Field Block Net for Accurate and Fast Object Detectioncited by 141
4 more
  1. 2020Normalized and Geometry-Aware Self-Attention Network for Image Captioningcited by 63
  2. 2018Polyp Segmentation in Colonoscopy Images Using Fully Convolutional Networkcited by 33
  3. 2013Automated polyp detection in colon capsule endoscopycited by 30
  4. 2019Psi-Net: Shape and boundary aware joint multi-task deep network for medical image segmentationcited by 30

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 7; 2022: 14; 2023: 14; 2024: 22; 2025: 14; 2026: 4.

75 papers.

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  1. 2021Polyp-PVT: Polyp Segmentation with Pyramid Vision Transformerscited by 159
  2. 2022Zoom In and Out: A Mixed-scale Triplet Network for Camouflaged Object Detectioncited by 145
  3. 2022Video Polyp Segmentation: A Deep Learning Perspectivecited by 82
  4. 2021Full-Duplex Strategy for Video Object Segmentationcited by 78
  5. 2021Automatic Polyp Segmentation via Multi-scale Subtraction Networkcited by 77
  6. 2023AutoSAM: Adapting SAM to Medical Images by Overloading the Prompt Encodercited by 70
  7. 2022Deep Gradient Learning for Efficient Camouflaged Object Detectioncited by 65
  8. 2022Implicit Motion Handling for Video Camouflaged Object Detectioncited by 60
  9. 2023VSCode: General Visual Salient and Camouflaged Object Detection with 2D Prompt Learningcited by 58
  10. 2024Vivim: a Video Vision Mamba for Medical Video Segmentationcited by 52
  11. 2023ZoomNeXt: A Unified Collaborative Pyramid Network for Camouflaged Object Detectioncited by 48
  12. 2021Fast Camouflaged Object Detection via Edge-based Reversible Re-calibration Networkcited by 42
38 more
  1. 2022Transformers in Medical Image Analysis: A Reviewcited by 41
  2. 2024A Survey of Camouflaged Object Detection and Beyondcited by 37
  3. 2023HQG-Net: Unpaired Medical Image Enhancement with High-Quality Guidancecited by 36
  4. 2021Depth Quality-Inspired Feature Manipulation for Efficient RGB-D Salient Object Detectioncited by 33
  5. 2022Camouflaged Object Detection via Context-aware Cross-level Fusioncited by 32
  6. 2022OSFormer: One-Stage Camouflaged Instance Segmentation with Transformerscited by 30
  7. 2022Assessing generalisability of deep learning-based polyp detection and segmentation methods through a computer vision challengecited by 27
  8. 2024SAM-COD: SAM-guided Unified Framework for Weakly-Supervised Camouflaged Object Detectioncited by 22
  9. 2023WeakPolyp: You Only Look Bounding Box for Polyp Segmentationcited by 21
  10. 2022Contrastive Transformer-based Multiple Instance Learning for Weakly Supervised Polyp Frame Detectioncited by 20
  11. 2023SimCol3D -- 3D Reconstruction during Colonoscopy Challengecited by 19
  12. 2024SALI: Short-term Alignment and Long-term Interaction Network for Colonoscopy Video Polyp Segmentationcited by 19
  13. 2024Hierarchical Graph Interaction Transformer with Dynamic Token Clustering for Camouflaged Object Detectioncited by 18
  14. 2023Shifting More Attention to Breast Lesion Segmentation in Ultrasound Videoscited by 16
  15. 2024Frontiers in Intelligent Colonoscopycited by 14
  16. 2023M2SNet: Multi-scale in Multi-scale Subtraction Network for Medical Image Segmentationcited by 13
  17. 2023A Survey on Deep Learning for Polyp Segmentation: Techniques, Challenges and Future Trendscited by 12
  18. 2024Explicit Motion Handling and Interactive Prompting for Video Camouflaged Object Detectioncited by 11
  19. 2024SAM-PM: Enhancing Video Camouflaged Object Detection using Spatio-Temporal Attentioncited by 11
  20. 2024When SAM2 Meets Video Camouflaged Object Segmentation: A Comprehensive Evaluation and Adaptationcited by 11
  21. 2025Reversible Unfolding Network for Concealed Visual Perception with Generative Refinementcited by 11
  22. 2022BoxPolyp:Boost Generalized Polyp Segmentation Using Extra Coarse Bounding Box Annotationscited by 10
  23. 2023Acquiring Weak Annotations for Tumor Localization in Temporal and Volumetric Datacited by 9
  24. 2024Inspiring the Next Generation of Segment Anything Models: Comprehensively Evaluate SAM and SAM 2 with Diverse Prompts Towards Context-Dependent Concepts under Different Scenescited by 9
  25. 2025CamSAM2: Segment Anything Accurately in Camouflaged Videoscited by 7
  26. 2024Diff-VPS: Video Polyp Segmentation via a Multi-task Diffusion Network with Adversarial Temporal Reasoningcited by 6
  27. 2024Self-Prompting Polyp Segmentation in Colonoscopy using Hybrid Yolo-SAM 2 Modelcited by 6
  28. 2022Trichomonas Vaginalis Segmentation in Microscope Imagescited by 5
  29. 2024Colorectal Polyp Segmentation in the Deep Learning Era: A Comprehensive Surveycited by 5
  30. 2021Guidance and Teaching Network for Video Salient Object Detectioncited by 4
  31. 2023Rethinking Polyp Segmentation from an Out-of-Distribution Perspectivecited by 4
  32. 2025BVINet: Unlocking Blind Video Inpainting with Zero Annotationscited by 4
  33. 2025Text-Promptable Propagation for Referring Medical Image Sequence Segmentationcited by 4
  34. 2024MAST: Video Polyp Segmentation with a Mixture-Attention Siamese Transformercited by 3
  35. 2024YOLO-MED : Multi-Task Interaction Network for Biomedical Imagescited by 3
  36. 2024HilbertMamba: Local-Global Reciprocal Network for Uterine Fibroid Segmentation in Ultrasound Videoscited by 2
  37. 2024Towards a Benchmark for Colorectal Cancer Segmentation in Endorectal Ultrasound Videos: Dataset and Model Developmentcited by 2
  38. 2025Assisted Refinement Network Based on Channel Information Interaction for Camouflaged and Salient Object Detectioncited by 2

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