Machine learningDeep learning / NLP / CV
弱监督目标检测
弱监督目标检测（Weakly Supervised Object Detection, WSOD）仅使用图像级标签（指示图像中存在哪些对象类别）来训练目标检测器，而无需昂贵的边界框标注。多实例学习（Multiple Instance Learning, MIL）公式允许模型仅通过分类信号发现每个对象类别的可能位置，从而显著降低了标注成本。
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来源
- Bilen, H., & Vedaldi, A. (2016). Weakly supervised deep detection networks. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2846–2854. DOI: 10.1109/CVPR.2016.311 ↗
- Tang, P., Wang, X., Bai, X., & Liu, W. (2017). Multiple instance detection network with online instance classifier refinement. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2843–2851. DOI: 10.1109/cvpr.2017.326 ↗
如何引用本页
ScholarGate. (2026, June 3). Weakly Supervised Object Detection (WSOD). ScholarGate. https://scholargate.app/zh/deep-learning/weakly-supervised-object-detection
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
- 图像分类深度学习↔ compare
- 实例分割深度学习↔ compare
- 目标检测深度学习↔ compare
- 半监督目标检测深度学习↔ compare
- Vision Transformer深度学习↔ compare