L2-Net: Deep Learning of Discriminative Patch Descriptor in Euclidean Space(2017)(一)
本文主要贡献： 1、提出了一种新的采样策略，使网络在少数的epoch迭代中，接触百万量级的训练样本； 2、基于局部图像块匹配问题，强调度量描述子的相对距离； 3、在中间特征图上加入额外的监督； 4、描述符的紧实性。 基于CNN的局部图像块匹配方法可以分为两类：一是，作为二分类问题，不存在明确的特征描述子概念，好处是准确率相对第二类高很多，但可移植性能差；二是，CNN输出学习
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相关文章
- 1. Application of deep learning in Industrial area
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