ModelNet40

doi:doi:10.57702/uexf99xg

ModelNet40

Point cloud registration is a crucial problem in computer vision and robotics. Existing methods either rely on matching local geometric features, which are sensitive to the pose differences, or leverage global shapes, which leads to inconsistency when facing distribution variances such as partial overlapping.

BibTex:

@dataset{Zhirong_Wu_and_Shuran_Song_and_Aditya_Khosla_and_Fisher_Yu_and_Linguang_Zhang_and_Xiaoou_Tang_and_Jianxiong_Xiao_2024,
    abstract = {Point cloud registration is a crucial problem in computer vision and robotics. Existing methods either rely on matching local geometric features, which are sensitive to the pose differences, or leverage global shapes, which leads to inconsistency when facing distribution variances such as partial overlapping.},
    author = {Zhirong Wu and Shuran Song and Aditya Khosla and Fisher Yu and Linguang Zhang and Xiaoou Tang and Jianxiong Xiao},
    doi = {10.57702/uexf99xg},
    institution = {No Organization},
    keyword = {'3D CAD Objects', '3D Data', '3D Matching', '3D Models', '3D Object', '3D Object Recognition', '3D Objects', '3D Point Cloud', '3D Point Cloud Registration', '3D Point Clouds', '3D Shape Classification', '3D Shape Segmentation', '3D Shapes', '3D computer vision', '3D models', '3D object', '3D object recognition', '3D objects', '3D point cloud', '3D point clouds', '3D shape recognition', '3D shapes', 'Benchmark', 'CAD Models', 'CAD models', 'Classification', 'Computer Vision', 'Computer vision', 'Computer-Aided Design', 'Convolutional Neural Networks', 'ModelNet40', 'NTU Dataset', 'Object Categories', 'Object Classification', 'Object Classiﬁcation', 'Object Recognition', 'Object recognition', 'Point Cloud', 'Point Cloud Registration', 'Point Clouds', 'Point clouds', 'Recognition', 'Segmentation', 'Semantic Segmentation', 'Shape Classification', 'Shape Recognition', 'Shape segmentation', 'ShapeNet', 'benchmarking', 'category annotations', 'classification', 'computer vision', 'mesh registration', 'object classification', 'object recognition', 'object understanding', 'point cloud', 'point clouds', 'segmentation', 'shape classification', 'shape recognition', 'shape retrieval', 'shape segmentation', 'synthetic dataset'},
    month = {nov},
    publisher = {TIB},
    title = {ModelNet40},
    url = {https://service.tib.eu/ldmservice/dataset/modelnet40},
    year = {2024}
}