S3DIS

doi:doi:10.57702/zi852631

S3DIS

The dataset used in the paper is a real-world 3D point cloud dataset, which is used for 3D shape classification, part segmentation, and shape retrieval tasks.

BibTex:

@dataset{Wei_Zhou_and_Xin_Cao_and_Xiaodan_Zhang_and_Xingxing_Hao_and_Dekui_Wang_and_Ying_He_2024,
    abstract = {The dataset used in the paper is a real-world 3D point cloud dataset, which is used for 3D shape classification, part segmentation, and shape retrieval tasks.},
    author = {Wei Zhou and Xin Cao and Xiaodan Zhang and Xingxing Hao and Dekui Wang and Ying He},
    doi = {10.57702/zi852631},
    institution = {No Organization},
    keyword = {'3D', '3D Indoor Scene Understanding', '3D Indoor Spaces', '3D Instance Segmentation', '3D Object Detection', '3D Point Clouds', '3D Scene Understanding', '3D Segmentation', '3D indoor scenes', '3D point cloud', '3D point clouds', '3D segmentation', 'Classification', 'Computer Vision', 'Gaussian Processes', 'Indoor Scene Understanding', 'Indoor Scenes', 'Instance Segmentation', 'Object Classiﬁcation', 'Point Cloud', 'Point Cloud Instance Segmentation', 'Point Clouds', 'S3DIS', 'Scene Understanding', 'Segmentation', 'Semantic Segmentation', 'classification', 'convexity-based segmentation', 'indoor environment', 'indoor point clouds', 'indoor scene understanding', 'instance segmentation', 'object recognition', 'point cloud', 'point cloud data', 'scene segmentation', 'scene understanding', 'semantic labels', 'semantic segmentation'},
    month = {nov},
    publisher = {TIB},
    title = {S3DIS},
    url = {https://service.tib.eu/ldmservice/dataset/s3dis},
    year = {2024}
}