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[論文解讀]D2-Net: A Trainable CNN for Joint Description and Detection of Local Features
時間 2020-12-23
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深度學習
pytorch
自動駕駛
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原文鏈接
文章鏈接:https://www.jianshu.com/p/b33c7c9ea2e7 以前好久的論文,這幾天整理資料也翻出來了。應該是CVPR19的論文,講的是同時做出來det和des。特徵點定位精度不高,速度也很慢,不過對光照等魯棒性非常高,如下圖所示。 但是這個方法的弱點非常明顯,定位精度不高,如下圖紅色圈出的地方,其實非常低的精度了。 實際上用這個進行重建的實驗結果表示還不如SIFT好。
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相關文章
1.
[論 文筆記]D2-Net: A Trainable CNN for Joint Description and Detection of Local Features
2.
[CVPR 2020] D3Feat: Joint Learning of Dense Detection and Description of 3D Local Features
3.
【點雲識別】D3Feat: Joint Learning of Dense Detection and Description of 3D Local Features(CVPR 2020 Oral)
4.
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5.
論文閱讀:Associative Embedding: End-to-End Learning for Joint Detection and Grouping
6.
ASLFeat: Learning Local Features of Accurate Shape and Localization &&2020
7.
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[論文解讀]ASLFeat: Learning Local Features of Accurate Shape and Localization
9.
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