mlsanityData to 7 Oct 2026

UCP-Net: Unstructured Contour Points for Instance Segmentation

arXiv 2109.07592 ↗First posted 15 Sep 2021cs.CVcited by 7

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Abstract (arXiv)

The goal of interactive segmentation is to assist users in producing segmentation masks as fast and as accurately as possible. Interactions have to be simple and intuitive and the number of interactions required to produce a satisfactory segmentation mask should be as low as possible. In this paper, we propose a novel approach to interactive segmentation based on unconstrained contour clicks for initial segmentation and segmentation refinement. Our method is class-agnostic and produces accurate segmentation masks (IoU > 85%) for a lower number of user interactions than state-of-the-art methods on popular segmentation datasets (COCO MVal, SBD and Berkeley).

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 13 of its 28 references that are in the map. First posted on arXiv 15 Sep 2021.

Builds on

13 of 28 references.

References · 13

  1. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  2. 2019EfficientNet: Rethinking Model Scaling for Convolutional Neural Networkscited by 6,415
  3. 2016Deep Interactive Object Selectioncited by 160
  4. 2017Deep Extreme Cut: From Extreme Points to Object Segmentationcited by 127
  5. 2020f-BRS: Rethinking Backpropagating Refinement for Interactive Segmentationcited by 117
  6. 2019Large-scale interactive object segmentation with human annotatorscited by 109
  7. 2017Extreme clicking for efficient object annotationcited by 80
  8. 2018Iteratively Trained Interactive Segmentationcited by 52
  9. 2020Getting to 99% Accuracy in Interactive Segmentationcited by 19
  10. 2017Interactive Video Object Segmentation in the Wildcited by 16
  11. 2018A Fully Convolutional Two-Stream Fusion Network for Interactive Image Segmentationcited by 15
  12. 2018Iterative Interaction Training for Segmentation Editing Networkscited by 14
1 more
  1. 2020FAIRS -- Soft Focus Generator and Attention for Robust Object Segmentation from Extreme Pointscited by 1

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Cited by year

Citing papers per year: 2023: 4; 2024: 3.

7 papers.

  1. 2023CFR-ICL: Cascade-Forward Refinement with Iterative Click Loss for Interactive Image Segmentationcited by 17
  2. 2024Adapting the Segment Anything Model During Usage in Novel Situationscited by 9
  3. 2023Guiding the Guidance: A Comparative Analysis of User Guidance Signals for Interactive Segmentation of Volumetric Imagescited by 5
  4. 2023Impact of Pseudo Depth on Open World Object Segmentation with Minimal User Guidancecited by 4
  5. 2023PiClick: Picking the desired mask from multiple candidates in click-based interactive segmentationcited by 4
  6. 2024Strike the Balance: On-the-Fly Uncertainty based User Interactions for Long-Term Video Object Segmentationcited by 4
  7. 2024Interactive Occlusion Boundary Estimation through Exploitation of Synthetic Datacited by 2