V2EX intersection-over-union

Intersection-over-Union

定义 Definition

Intersection-over-Union(IoU):在计算机视觉中衡量两个区域(常见为两个边界框或两个分割掩膜)重叠程度的指标,定义为交集面积 ÷ 并集面积。取值范围通常为 0 到 1,越接近 1 表示重叠越高。(在一些任务里也可能扩展到 0100% 以百分比表示。)

发音 Pronunciation (IPA)

/ntskn ovr junin/

例句 Examples

The IoU between the predicted box and the ground-truth box is 0.72.
预测框与真实标注框的 IoU 是 0.72。

We report mean average precision at an IoU threshold of 0.5 to evaluate the detector’s performance under consistent matching criteria.
我们在 IoU 阈值为 0.5 的条件下报告平均精度均值,以在一致的匹配标准下评估检测器的性能。

词源 Etymology

该术语由三个常用词组合而成:intersection(交集)+ over(除以/相对于)+ union(并集)。它把集合论中的“交集/并集”思想直接用于图像中的区域重叠计算,因此在目标检测与语义分割等领域成为标准指标与匹配规则(例如用某个 IoU 阈值决定预测是否算“命中”)。

相关词 Related Words

  • Intersection
  • Union
  • Overlap
  • Jaccard
  • Bounding
  • Detection
  • Segmentation
  • Threshold
  • Precision
  • Recall
  • 文学/经典著作中的用例 Literary Works

    • Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks(2015,Ren et al.):将 IoU 用作候选框与真实框的匹配标准与训练信号的重要组成部分。
    • You Only Look Once (YOLO) 系列论文(2016):在评估检测效果时与 mAP 等指标一起使用 IoU 阈值。
    • Mask R-CNN(2017,He et al.):在实例分割与检测评估中广泛使用 IoU/基于 IoU 的匹配规则。
    • Computer Vision: A Modern Approach(Forsyth & Ponce):在讲解目标检测/重叠度度量时涉及与 IoU(Jaccard/重叠系数)同类的思想与指标。
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