SuperPoint:高效的神经特征检测器和描述符

上传者: 42126668 | 上传时间: 2022-05-25 14:55:56 | 文件大小: 138.8MB | 文件类型: ZIP
超点 这是“ SuperPoint:自我监督的兴趣点检测和描述”的Tensorflow实现。 Daniel DeTone,Tomasz Malisiewicz,Andrew Rabinovich。 。 HPatches上的结果 检测器评估 HPatches的可重复性,计算出在成对图像之间共有300个点,并且NMS为4: 照明变化 观点改变 SuperPoint(我们的实现) 0.662 0.674 SuperPoint( ) 0.641 0.621 快速地 0.576 0.625 哈里斯 0.630 0.755 施 0.584 0.629 描述符评估 对HPatch进行的单应估计法,计算出的最大成对图像之间共检测到1000个点,正确性阈值为3,NMS为8: 照明变化 观点改变 SuperPoint(我们的实现) 0.965 0.712 SuperPoint

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