{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T06:33:17Z","timestamp":1759991597737,"version":"3.37.3"},"reference-count":29,"publisher":"Springer Science and Business Media LLC","issue":"7","license":[{"start":{"date-parts":[[2023,9,12]],"date-time":"2023-09-12T00:00:00Z","timestamp":1694476800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,9,12]],"date-time":"2023-09-12T00:00:00Z","timestamp":1694476800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"Sichuan Province Foreign and Overseas High-end Talent Introduction Program","award":["22RCYJ0024"],"award-info":[{"award-number":["22RCYJ0024"]}]},{"DOI":"10.13039\/100012542","name":"Sichuan Province Science and Technology Support Program","doi-asserted-by":"publisher","award":["2022YFG0198"],"award-info":[{"award-number":["2022YFG0198"]}],"id":[{"id":"10.13039\/100012542","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Intell Manuf"],"published-print":{"date-parts":[[2024,10]]},"DOI":"10.1007\/s10845-023-02200-6","type":"journal-article","created":{"date-parts":[[2023,9,12]],"date-time":"2023-09-12T16:02:13Z","timestamp":1694534533000},"page":"3273-3289","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["CD3IS: cross dimensional 3D instance segmentation network for production workshop"],"prefix":"10.1007","volume":"35","author":[{"given":"Zaizuo","family":"Tang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0529-391X","authenticated-orcid":false,"given":"Guangzhu","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ruili","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhenlian","family":"Miao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Manna","family":"Dai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yujun","family":"Ma","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaojuan","family":"Liao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,9,12]]},"reference":[{"key":"2200_CR1","doi-asserted-by":"crossref","unstructured":"Bolya, D., Zhou, C., Xiao, F., & Lee, Y. J. (2019). YOLACT: Real-time instance segmentation. In Proceedings of IEEE\/CVF international conference on computer vision (ICCV) (pp. 9156\u20139165).","DOI":"10.1109\/ICCV.2019.00925"},{"key":"2200_CR2","doi-asserted-by":"crossref","unstructured":"Chen, S., Fang, J., Zhang, Q., Liu, W., & Wang, X. (2021). Hierarchical aggregation for 3D instance segmentation. In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition (CVPR) (pp. 15467\u201315476).","DOI":"10.1109\/ICCV48922.2021.01518"},{"key":"2200_CR3","doi-asserted-by":"crossref","unstructured":"Chen, Y.-N., Dai, H., & Ding, Y. (2022). Pseudo-stereo for monocular 3D object detection in autonomous driving. In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition (CVPR) (pp. 887\u2013897)","DOI":"10.1109\/CVPR52688.2022.00096"},{"key":"2200_CR4","doi-asserted-by":"crossref","unstructured":"Cheng, T., Wang, X., Huang, L., & Liu, W. (2020). Boundary-preserving mask R-CNN. In Proceedings of the European conference on computer vision (ECCV) (pp. 660\u2013676).","DOI":"10.1007\/978-3-030-58568-6_39"},{"key":"2200_CR5","doi-asserted-by":"crossref","unstructured":"Cheng, Y., Lin, R., Zhen, P., Hou, T., Ng, C. W., Chen, H. B., Yu, H., & Wong, N. (2022). FASSST: Fast attention based single-stage segmentation net for real-time instance segmentation. In Proceedings of the 2022 IEEE\/CVF winter conference on applications of computer vision, WACV 2022 (pp. 2714\u20132722)","DOI":"10.1109\/WACV51458.2022.00277"},{"key":"2200_CR6","doi-asserted-by":"crossref","unstructured":"Cordts. M., Omran, M., Ramos, S., Rehfeld, T., Enzweiler, M., Benenson, R., Franke, U., Roth, S., & Schiele, B. (2016). The cityscapes dataset for semantic urban scene understanding. In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition (CVPR)","DOI":"10.1109\/CVPR.2016.350"},{"key":"2200_CR7","unstructured":"Doll, P., Girshick, R., & Ai, F. (2017). Mask R-CNN. In Proceedings of the IEEE international conference on computer vision (ICCV) (pp. 2961\u20132969)."},{"issue":"January","key":"2200_CR8","first-page":"2366","volume":"3","author":"D Eigen","year":"2014","unstructured":"Eigen, D., Puhrsch, C., & Fergus, R. (2014). Depth map prediction from a single image using a multi-scale deep network. Advances in Neural Information Processing Systems, 3(January), 2366\u20132374.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"2200_CR9","doi-asserted-by":"crossref","unstructured":"Everingham, M., Van Gool, L., Williams, C. K.,\nWinn, J.,  and Zisserman, A. (2010). The PASCAL visual object classes (voc) challenge.\nInternational journal of\ncomputer vision, 88(2), 303\u2013338.","DOI":"10.1007\/s11263-009-0275-4"},{"issue":"2","key":"2200_CR10","doi-asserted-by":"publisher","first-page":"1572","DOI":"10.1109\/TITS.2020.3025067","volume":"23","author":"J Gao","year":"2022","unstructured":"Gao, J., Chen, Y., Junior, J. M., Wang, C., & Li, J. (2022). Rapid extraction of urban road guardrails from mobile LiDAR point clouds. IEEE Transactions on Intelligent Transportation Systems, 23(2), 1572\u20131577.","journal-title":"IEEE Transactions on Intelligent Transportation Systems"},{"issue":"2","key":"2200_CR11","doi-asserted-by":"publisher","first-page":"661","DOI":"10.1109\/TCSVT.2020.2985420","volume":"31","author":"N Gao","year":"2021","unstructured":"Gao, N., Shan, Y., Wang, Y., Zhao, X., & Huang, K. (2021). SSAP: Single-shot instance segmentation with affinity pyramid. IEEE Transactions on Circuits and Systems for Video Technology, 31(2), 661\u2013673. https:\/\/doi.org\/10.1109\/TCSVT.2020.2985420","journal-title":"IEEE Transactions on Circuits and Systems for Video Technology"},{"key":"2200_CR12","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2021.108245","volume":"115","author":"R Hou","year":"2022","unstructured":"Hou, R., Chen, G., Han, Y., Tang, Z., & Ru, Q. (2022). Multi-modal feature fusion for 3D object detection in the production workshop. Applied Soft Computing, 115, 108245.","journal-title":"Applied Soft Computing"},{"issue":"8","key":"2200_CR13","doi-asserted-by":"publisher","first-page":"5171","DOI":"10.1109\/TII.2021.3122801","volume":"18","author":"C Huang","year":"2022","unstructured":"Huang, C., Wu, Z., Wen, J., Xu, Y., Jiang, Q., & Wang, Y. (2022). Abnormal event detection using deep contrastive learning for intelligent video surveillance system. IEEE Transactions on Industrial Informatics, 18(8), 5171\u20135179.","journal-title":"IEEE Transactions on Industrial Informatics"},{"key":"2200_CR14","doi-asserted-by":"crossref","unstructured":"Jiang, L., Zhao, H., Shi, S., Liu, S., Fu, C.W., & Jia, J. (2020). PointGroup: Dual-set point grouping for 3D instance segmentation. In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition (CVPR) (pp. 4866\u20134875).","DOI":"10.1109\/CVPR42600.2020.00492"},{"key":"2200_CR15","doi-asserted-by":"crossref","unstructured":"Lee, Y., & Park, J. (2020). CenterMask: Real-time anchor-free instance segmentation. In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition (CVPR) (pp. 13903\u201313912).","DOI":"10.1109\/CVPR42600.2020.01392"},{"key":"2200_CR16","doi-asserted-by":"crossref","unstructured":"Lin, T.-Y., Doll\u00e1r, P., Girshick, R., He, K., Hariharan, B., & Belongie, S. (2017). Feature pyramid networks for object detection. In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition (CVPR) (pp. 2117\u20132125).","DOI":"10.1109\/CVPR.2017.106"},{"issue":"2","key":"2200_CR17","doi-asserted-by":"publisher","first-page":"318","DOI":"10.1109\/TPAMI.2018.2858826","volume":"42","author":"TY Lin","year":"2020","unstructured":"Lin, T. Y., Goyal, P., Girshick, R., He, K., & Dollar, P. (2020). Focal loss for dense object detection. IEEE Transactions on Pattern Analysis and Machine Intelligence, 42(2), 318\u2013327. https:\/\/doi.org\/10.1109\/TPAMI.2018.2858826","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"2200_CR18","doi-asserted-by":"crossref","unstructured":"Lin, T. Y., Maire, M., Belongie, S., Hays, J., Perona, P., Ramanan, D., Dollar, P.,& Zitnick, L. (2014). Microsoft coco: Common objects in context. In Proceedings of the European Conference on Computer Vision (ECCV) (pp. 740\u2013755).","DOI":"10.1007\/978-3-319-10602-1_48"},{"key":"2200_CR19","doi-asserted-by":"crossref","unstructured":"Peng, S., Jiang, W., Pi, H., Li, X., Bao, H., & Zhou, X. (2020). Deep snake for real-time instance segmentation. In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition (CVPR) (pp. 8530\u20138539)","DOI":"10.1109\/CVPR42600.2020.00856"},{"key":"2200_CR20","doi-asserted-by":"publisher","first-page":"124","DOI":"10.1016\/j.neucom.2021.11.104","volume":"472","author":"C Shang","year":"2022","unstructured":"Shang, C., Li, H., Meng, F., Qiu, H., Wu, Q., Xu, L., & Ngan, K. N. (2022). Instance-level context attention network for instance segmentation. Neurocomputing, 472, 124\u2013137.","journal-title":"Neurocomputing"},{"key":"2200_CR21","doi-asserted-by":"crossref","unstructured":"Shi, Y., Li, Y., Tan, X., Feng, J., Ding, E., & Wen, S. (2020). Monocular 3D object detection via feature domain adaptation. In Proceedings of the European conference on computer vision (ECCV) (pp. 17\u201334).","DOI":"10.1007\/978-3-030-58545-7_2"},{"issue":"2","key":"2200_CR22","first-page":"701","volume":"10","author":"HAB Sulaiman","year":"2015","unstructured":"Sulaiman, H. A. B., Othman, M. A., Aziz, M. Z. A. A., & Bade, A. (2015). Implementation of axis-aligned bounding box for opengl 3D virtual environment. ARPN J. Eng. Appl. Sci., 10(2), 701\u2013708.","journal-title":"ARPN J. Eng. Appl. Sci."},{"key":"2200_CR23","doi-asserted-by":"crossref","unstructured":"Tang, L., Zhan, Y., Chen, Z., Yu, B., & Tao, D. (2022). Contrastive boundary learning for point cloud segmentation. In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition (CVPR) (pp. 8489\u20138499).","DOI":"10.1109\/CVPR52688.2022.00830"},{"key":"2200_CR24","doi-asserted-by":"publisher","first-page":"104858","DOI":"10.1016\/j.engappai.2022.104858","volume":"112","author":"Z Tang","year":"2022","unstructured":"Tang, Z., Chen, G., Han, Y., Liao, X., Ru, Q., & Wu, Y. (2022). Bi-stage multi-modal 3D instance segmentation method for production workshop scene. Engineering Applications of Artificial Intelligence, 112, 104858.","journal-title":"Engineering Applications of Artificial Intelligence"},{"key":"2200_CR25","doi-asserted-by":"crossref","unstructured":"Vu, T., Kim, K., Luu, T. M., Nguyen, X. T., & Yoo, C. D. (2022). SoftGroup for 3D instance segmentation on point clouds. In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition (CVPR) (pp. 2708\u20132717).","DOI":"10.1109\/CVPR52688.2022.00273"},{"key":"2200_CR26","first-page":"13364","volume":"34","author":"L Wang","year":"2021","unstructured":"Wang, L., Zhang, L., Zhu, Y., Zhang, Z., He, T., Li, M., & Xue, X. (2021). Progressive coordinate transforms for monocular 3D object detection. Advances in Neural Information Processing Systems, 34, 13364\u201313377.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"2200_CR27","doi-asserted-by":"crossref","unstructured":"Yu, F., Wang, D., Shelhamer, E., & Darrell, T. (2018). Deep layer aggregation. In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition (CVPR) (pp. 2403\u20132412).","DOI":"10.1109\/CVPR.2018.00255"},{"key":"2200_CR28","doi-asserted-by":"crossref","unstructured":"Zhang, T., Wei, S., & Ji, S. (2022). E2EC\u202f: An end-to-end contour-based method for high-quality high-speed instance segmentation. In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition (CVPR) (pp. 4443\u20134452).","DOI":"10.1109\/CVPR52688.2022.00440"},{"issue":"2","key":"2200_CR29","doi-asserted-by":"publisher","first-page":"1377","DOI":"10.1109\/TII.2021.3061419","volume":"18","author":"X Zhou","year":"2022","unstructured":"Zhou, X., Xu, X., Liang, W., Zeng, Z., Shimizu, S., Yang, L. T., & Jin, Q. (2022). Intelligent small object detection for digital twin in smart manufacturing with industrial cyber-physical systems. IEEE Transactions on Industrial Informatics, 18(2), 1377\u20131386.","journal-title":"IEEE Transactions on Industrial Informatics"}],"container-title":["Journal of Intelligent Manufacturing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10845-023-02200-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10845-023-02200-6\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10845-023-02200-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,5]],"date-time":"2024-09-05T12:30:45Z","timestamp":1725539445000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10845-023-02200-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,9,12]]},"references-count":29,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2024,10]]}},"alternative-id":["2200"],"URL":"https:\/\/doi.org\/10.1007\/s10845-023-02200-6","relation":{},"ISSN":["0956-5515","1572-8145"],"issn-type":[{"type":"print","value":"0956-5515"},{"type":"electronic","value":"1572-8145"}],"subject":[],"published":{"date-parts":[[2023,9,12]]},"assertion":[{"value":"8 May 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 August 2023","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 September 2023","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}