NPM3D dataset with instance labels used in paper "Toward Accurate Instance Segmentation in Large-scale LiDAR Point Clouds"
Description
NPM3D (https://npm3d.fr/paris-carla-3d) consists of mobile laser scanning (MLS) point clouds collected in four different regions in the French cities of Paris and Lille, where each point has been annotated with two labels: one that assigns it to one out of 10 semantic categories and another one that assigns it to an object instance. When inspecting the data, we found 9 cases where multiple tree instances had not been separated correctly (i.e., they had the same ground truth instance label). These cases were manually corrected using the CloudCompare software (https://www.cloudcompare.org), and 35 individual tree instances were obtained. Our variant of the dataset with 10 semantic categories and enhanced instance labels is publicly available.
Files
Files
(5.3 GB)
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md5:13545bfed23f68d5fc071f67a5796e73
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md5:7d819d82185a402a5a97404610a75373
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md5:500049e818ab279e43e675994dbdf713
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md5:08e843c0c66934d3c86f4f8cc489cfc3
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md5:9637d441c9c747fb086ab089d4d10a52
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md5:aa0e73c4bc51f1891c724d5465ccc276
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md5:07e0263d55125832b938afcdbbfa40b0
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md5:0877f2a1612d923f235bdb2d5dff2c68
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Additional details
References
- Toward Accurate Instance Segmentation in Large-scale LiDAR Point Clouds