mlsanityData to 7 Oct 2026

Enhanced-alignment Measure for Binary Foreground Map Evaluation

arXiv 1805.10421 ↗First posted 26 May 2018cs.CVcited by 370

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Abstract (arXiv)

The existing binary foreground map (FM) measures to address various types of errors in either pixel-wise or structural ways. These measures consider pixel-level match or image-level information independently, while cognitive vision studies have shown that human vision is highly sensitive to both global information and local details in scenes. In this paper, we take a detailed look at current binary FM evaluation measures and propose a novel and effective E-measure (Enhanced-alignment measure). Our measure combines local pixel values with the image-level mean value in one term, jointly capturing image-level statistics and local pixel matching information. We demonstrate the superiority of our measure over the available measures on 4 popular datasets via 5 meta-measures, including ranking models for applications, demoting generic, random Gaussian noise maps, ground-truth switch, as well as human judgments. We find large improvements in almost all the meta-measures. For instance, in terms of application ranking, we observe improvementrangingfrom9.08% to 19.65% compared with other popular measures.

Key facts. Cited by 370 papers in the map (data through 7 Oct 2026). First posted on arXiv 26 May 2018.

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Citing papers per year: 2021: 60; 2022: 66; 2023: 67; 2024: 70; 2025: 55; 2026: 52.

370 papers.

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  12. 2021Automatic Polyp Segmentation via Multi-scale Subtraction Networkcited by 77
38 more
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  11. 2023DFormer: Rethinking RGBD Representation Learning for Semantic Segmentationcited by 58
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  14. 2022A Unified Transformer Framework for Group-based Segmentation: Co-Segmentation, Co-Saliency Detection and Video Salient Object Detectioncited by 51
  15. 2023ZoomNeXt: A Unified Collaborative Pyramid Network for Camouflaged Object Detectioncited by 48
  16. 2021CAVER: Cross-Modal View-Mixed Transformer for Bi-Modal Salient Object Detectioncited by 47
  17. 2023Advances in Deep Concealed Scene Understandingcited by 47
  18. 2021TriTransNet: RGB-D Salient Object Detection with a Triplet Transformer Embedding Networkcited by 45
  19. 2022Weakly-Supervised Camouflaged Object Detection with Scribble Annotationscited by 43
  20. 2023CaraNet: Context Axial Reverse Attention Network for Segmentation of Small Medical Objectscited by 43
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  22. 2021Fast Camouflaged Object Detection via Edge-based Reversible Re-calibration Networkcited by 42
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  26. 2022Does Thermal Really Always Matter for RGB-T Salient Object Detection?cited by 37
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  29. 2021RGB-D Salient Object Detection via 3D Convolutional Neural Networkscited by 36
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  31. 2021Depth Quality-Inspired Feature Manipulation for Efficient RGB-D Salient Object Detectioncited by 33
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  36. 2023Each Test Image Deserves A Specific Prompt: Continual Test-Time Adaptation for 2D Medical Image Segmentationcited by 29
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  38. 2023MEGANet: Multi-Scale Edge-Guided Attention Network for Weak Boundary Polyp Segmentationcited by 28

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