{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T18:24:28Z","timestamp":1742927068747,"version":"3.40.3"},"publisher-location":"Cham","reference-count":30,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031463105"},{"type":"electronic","value":"9783031463112"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023]]},"DOI":"10.1007\/978-3-031-46311-2_20","type":"book-chapter","created":{"date-parts":[[2023,10,28]],"date-time":"2023-10-28T19:01:50Z","timestamp":1698519710000},"page":"235-246","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["3D Object Recognition Based on Point Cloud Geometry Construction and Embeddable Attention"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0170-8030","authenticated-orcid":false,"given":"Jingshan","family":"Shi","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7554-5123","authenticated-orcid":false,"given":"Zhuyan","family":"Guo","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0001-1476-4402","authenticated-orcid":false,"given":"Shujia","family":"Cheng","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0002-7657-3924","authenticated-orcid":false,"given":"Yuhan","family":"Liu","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5729-9718","authenticated-orcid":false,"given":"Mandun","family":"Zhang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1977-4674","authenticated-orcid":false,"given":"Zhidong","family":"Xiao","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,10,29]]},"reference":[{"key":"20_CR1","doi-asserted-by":"publisher","first-page":"163775","DOI":"10.1109\/ACCESS.2020.3021191","volume":"8","author":"CH Chiang","year":"2020","unstructured":"Chiang, C.H., Kuo, C.H., Lin, C.C., Chiang, H.T.: 3D point cloud classification for autonomous driving via dense-residual fusion network. IEEE Access 8, 163775\u2013163783 (2020)","journal-title":"IEEE Access"},{"issue":"3","key":"20_CR2","doi-asserted-by":"publisher","first-page":"101929","DOI":"10.1016\/j.rcim.2019.101929","volume":"64","author":"L Yang","year":"2020","unstructured":"Yang, L., Liu, Y., Peng, J., Liang, Z.: A novel system for off-line 3D seam extraction and path planning based on point cloud segmentation for arc welding robot. Robot. Comput. Integr. Manuf. 64(3), 101929 (2020)","journal-title":"Robot. Comput. Integr. Manuf."},{"key":"20_CR3","first-page":"1","volume":"1","author":"D Bolkas","year":"2020","unstructured":"Bolkas, D., Chiampi, J., Chapman, J., Pavill, V.F.: Creating a virtual reality environment with a fusion of sUAS and TLS point-clouds. Int. J. Image Data Fusion 1, 1\u201326 (2020)","journal-title":"Int. J. Image Data Fusion"},{"key":"20_CR4","unstructured":"Qi, C.R., Su, H., Mo, K., Guibas, L.J.: PointNet: deep learning on point sets for 3D classification and segmentation. IEEE (2017)"},{"key":"20_CR5","unstructured":"Qi, C.R., Li, Y., Hao, S., Guibas, L.J.: PointNet++: deep hierarchical feature learning on point sets in a metric space (2017)"},{"key":"20_CR6","doi-asserted-by":"crossref","unstructured":"Yan, X., Zheng, C., Li, Z., Wang, S., Cui, S.: PointASNL: robust point clouds processing using nonlocal neural networks with adaptive sampling. IEEE (2020)","DOI":"10.1109\/CVPR42600.2020.00563"},{"key":"20_CR7","unstructured":"Li, Y., Bu, R., Sun, M., Wu, W., Di, X., Chen, B.: PointCNN: convolution on x-transformed points. In: Neural Information Processing Systems (2018)"},{"key":"20_CR8","doi-asserted-by":"crossref","unstructured":"Wu, W., Qi, Z., Li, F.: PointConv: deep convolutional networks on 3D point clouds. In: 2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2019)","DOI":"10.1109\/CVPR.2019.00985"},{"key":"20_CR9","doi-asserted-by":"crossref","unstructured":"Thomas, H., Qi, C.R., Deschaud, J.E., Marcotegui, B., Guibas, L.J.: KpConv: flexible and deformable convolution for point clouds (2019)","DOI":"10.1109\/ICCV.2019.00651"},{"key":"20_CR10","doi-asserted-by":"crossref","unstructured":"Yan, S., et al.: Implicit autoencoder for point cloud self-supervised representation learning. arXiv e-prints (2022)","DOI":"10.1109\/ICCV51070.2023.01336"},{"issue":"2","key":"20_CR11","doi-asserted-by":"publisher","first-page":"13","DOI":"10.1007\/s41095-021-0229-5","volume":"7","author":"MH Guo","year":"2021","unstructured":"Guo, M.H., Cai, J.X., Liu, Z.N., Mu, T.J., Martin, R.R., Hu, S.M.: PCT: point cloud transformer. Comput. Visual Media 7(2), 13 (2021)","journal-title":"Comput. Visual Media"},{"key":"20_CR12","unstructured":"Wu, Z., et al.: 3D ShapeNets: a deep representation for volumetric shapes. In: 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2015)"},{"key":"20_CR13","doi-asserted-by":"crossref","unstructured":"Atzmon, M., Maron, H., Lipman, Y.: Point convolutional neural networks by extension operators. ACM Trans. Graph. 37(4CD), 71.1\u2013 71.12 (2018)","DOI":"10.1145\/3197517.3201301"},{"key":"20_CR14","first-page":"8778","volume":"33","author":"X Liu","year":"2019","unstructured":"Liu, X., Han, Z., Liu, Y.S., Zwicker, M.: Point2Sequence: learning the shape representation of 3D point clouds with an attention-based sequence to sequence network. Proc. AAAI Conf. Artif. Intell. 33, 8778\u20138785 (2019)","journal-title":"Proc. AAAI Conf. Artif. Intell."},{"key":"20_CR15","unstructured":"Fan, B., Pan, C., Xiang, S., Liu, Y.: Relation-shape convolutional neural network for point cloud analysis (2019)"},{"key":"20_CR16","unstructured":"Qiu, S., Anwar, S., Barnes, N.: Geometric back-projection network for point cloud classification (2019)"},{"key":"20_CR17","doi-asserted-by":"crossref","unstructured":"Engel, N., Belagiannis, V., Dietmayer, K.: Point transformer (2020)","DOI":"10.1109\/ACCESS.2021.3116304"},{"key":"20_CR18","doi-asserted-by":"crossref","unstructured":"Liu, Z., Hu, H., Cao, Y., Zhang, Z., Tong, X.: A closer look at local aggregation operators in point cloud analysis (2020)","DOI":"10.1007\/978-3-030-58592-1_20"},{"key":"20_CR19","unstructured":"Han, X.F., Kuang, Y.J., Xiao, G.Q.: Point cloud learning with transformer (2021)"},{"key":"20_CR20","doi-asserted-by":"crossref","unstructured":"Zhao, H., Jiang, L., Jia, J., Torr, P., Koltun, V.: Point transformer (2020)","DOI":"10.1109\/ICCV48922.2021.01595"},{"key":"20_CR21","doi-asserted-by":"crossref","unstructured":"Ran, H., Liu, J., Wang, C.: Surface representation for point clouds (2022)","DOI":"10.1109\/CVPR52688.2022.01837"},{"key":"20_CR22","doi-asserted-by":"crossref","unstructured":"Liu, S., Liu, D., Chen, C., Xu, C.: SGCNN for 3D point cloud classification. In: 2022 14th International Conference on Machine Learning and Computing (ICMLC) (2022)","DOI":"10.1145\/3529836.3529847"},{"key":"20_CR23","doi-asserted-by":"crossref","unstructured":"Lu, D., Xie, Q., Xu, L., Li, J.: 3DCTN: 3D convolution-transformer network for point cloud classification (2022)","DOI":"10.1109\/TITS.2022.3198836"},{"key":"20_CR24","doi-asserted-by":"crossref","unstructured":"Xu, Y., Fan, T., Xu, M., Long, Z., Yu, Q.: SpiderCNN: deep learning on point sets with parameterized convolutional filters (2018)","DOI":"10.1007\/978-3-030-01237-3_6"},{"key":"20_CR25","doi-asserted-by":"crossref","unstructured":"Uy, M.A., Pham, Q.H., Hua, B.S., Nguyen, T., Yeung, S.K.: Revisiting point cloud classification: a new benchmark dataset and classification model on real-world data. IEEE (2020)","DOI":"10.1109\/ICCV.2019.00167"},{"key":"20_CR26","unstructured":"Goyal, A., Law, H., Liu, B., Newell, A., Deng, J.: Revisiting point cloud shape classification with a simple and effective baseline (2021)"},{"key":"20_CR27","doi-asserted-by":"crossref","unstructured":"Qiu, S., Anwar, S., Barnes, N.: Dense-resolution network for point cloud classification and segmentation (2020)","DOI":"10.1109\/WACV48630.2021.00386"},{"key":"20_CR28","doi-asserted-by":"publisher","first-page":"4436","DOI":"10.1109\/TIP.2021.3072214","volume":"30","author":"S Cheng","year":"2021","unstructured":"Cheng, S., Chen, X., He, X., Liu, Z., Bai, X.: PRA-Net: point relation-aware network for 3D point cloud analysis. IEEE Trans. Image Process. 30, 4436\u20134448 (2021)","journal-title":"IEEE Trans. Image Process."},{"key":"20_CR29","doi-asserted-by":"crossref","unstructured":"Hamdi, A., Giancola, S., Li, B., Thabet, A., Ghanem, B.: MVTN: multi-view transformation network for 3D shape recognition (2020)","DOI":"10.1109\/ICCV48922.2021.00007"},{"key":"20_CR30","doi-asserted-by":"crossref","unstructured":"Klokov, R., Lempitsky, V.: Escape from cells: deep Kd-networks for the recognition of 3D point cloud models. IEEE (2017)","DOI":"10.1109\/ICCV.2017.99"}],"container-title":["Lecture Notes in Computer Science","Image and Graphics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-46311-2_20","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,1]],"date-time":"2024-11-01T00:19:43Z","timestamp":1730420383000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-46311-2_20"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031463105","9783031463112"],"references-count":30,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-46311-2_20","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"29 October 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICIG","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Image and Graphics","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Nanjing","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 September 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24 September 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icig2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/icig2023.csig.org.cn\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Conference Management Toolkit","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"409","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"166","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"41% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}