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2D3D-MatchNet: Learning to Match Keypoints Across 2D Image and 3D Point Cloud
時間 2021-08-15
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整體網絡架構是這樣: 基本上是堆積起來的網絡,一共三條分支 1:image 2d feature 提取 2:正樣本point cloud pointnet feature提取,3:負樣本point cloud pointnet feature 提取 ,最後直接soft-margin triplet loss。 2d輸入的是image 的patches, 3d輸入的是volume。 2d使用
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相關文章
1.
【點雲識別】Learning to Segment 3D Point Clouds in 2D Image Space (CVPR 2020)
2.
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3.
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VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection
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10.
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