[论文解读]ASLFeat: Learning Local Features of Accurate Shape and Localization
先总结一下： 这个文章是对D2Net的更进一步，主要解决了D2Net的痛点——keypoint太不准了。我实际用D2Net进行三维重建就感受到，D2Net并不是高精度的像素级匹配，而更像是图像检索的DELF。它在4pixel threshold 的精度以下完全没法跟传统的SIFT之类比，只有当阈值放大才能有特别出众的效果。 这个文章解决了这个痛点，而且benchmark看起来效果也是特别好。 贡献
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相关文章
- 1. ASLFeat: Learning Local Features of Accurate Shape and Localization &&2020
- 2. 论文阅读-《Learning Deep Features for Discriminative Localization》
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- 4. Learning Deep Features for Discriminative Localization论文笔记
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