Weakly Supervised Object Detection via Object-Specific Pixel Gradient
paper:https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8333805 简介：目前先有的弱监督目标检测方法大多将其作为一个多示例问题，产生候选区域，然后分类器判断类别的方式进行获得位置信息。本文作者利用图像梯度，提出了一种新的定位目标框的方式。 1.在目标分类网络中，目标所在区域反映到特征上是显著的，基于这个出发点，展开。 首先
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相关文章
- 1. 简读：Object-Aware Instance Labeling for Weakly Supervised Object Detection
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