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ASLFeat: Learning Local Features of Accurate Shape and Localization &&2020
時間 2020-12-23
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通訊作者:Long Quan 第一作者:Zixin Luo 研究機構:港科大,清華,快手 自己的想法: 論文解決的問題 論文提出的方法解決了局部特徵檢測器和描述子的兩個侷限性: 在密集特徵提取過程中,往往忽略了特徵點的局部形狀(尺度、方向等)的估計能力,而形狀感知是獲得較強幾何不變性的關鍵。 檢測到的特徵點的定位精度不足以可靠地恢復相機的幾何結構,這已成爲3D重建等任務的瓶頸。 現有方法的不足 &
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相關文章
1.
[論文解讀]ASLFeat: Learning Local Features of Accurate Shape and Localization
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.
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6.
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8.
《SpineNet: Learning Scale-Permuted Backbone for Recognition and Localization》
9.
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