…In moving object segmentation of point cloud sequences, one has to provide motion labels for each point of the test sequences 11-21. We map all moving-x classes of the original SemanticKITTI semantic segmentation benchmark to a single moving object class. Citation Citation. More information on the task and the metric, you can find in our publication related to the task: @article{chen2021ral, title={{Moving Object Segmentation in 3D LiDAR Data: A Learning-based Approach
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…created in the frame of the 3DTeethSeg 2022 MICCAI challenge to boost the research field and inspire the 3D vision research community to work on intra-oral 3D scans analysis such as teeth identification, segmentation
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IntrA is an open-access 3D intracranial aneurysm dataset that makes the application of points-based and mesh-based classification and segmentation models available. reconstruction. 103 3D models of entire brain vessels are collected by reconstructing scanned 2D MRA images of patients (the raw 2D MRA images are not published due to medical ethics). 1909 blood vessel segments are generated automatically from the complete models, including 1694 healthy vessel segments and 215 aneurysm segments for diagnosis. 116 aneurysm segments are divided and annotated manually by medical experts; the scale of each aneurysm segment is based on the need for a preoperative examination. Geodesic distance matrices are computed and included for each annotated 3D segment, because the expression of the geodesic distance is more accurate than Euclidean distance according to the shape of vessels
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…contains 20 common workshop tools, and for each object: - a watertight triangular surface mesh; - a synthetic colored surface point-cloud; - ground truth inertial parameters; - ground truth part-level segmentation by Open3D element vertex 2000 property float32 x property float32 y property float32 z property float32 red property float32 green property float32 blue property uint8 segmentation please cite our paper: @inproceedings{Nadeau_PartSegForInertialIdent_2023, AUTHOR = {Philippe Nadeau AND Matthew Giamou AND Jonathan Kelly}, TITLE = { {The Sum of Its Parts: Visual Part Segmentation
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