{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,10]],"date-time":"2026-02-10T14:22:15Z","timestamp":1770733335639,"version":"3.49.0"},"publisher-location":"Cham","reference-count":29,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031586750","type":"print"},{"value":"9783031586767","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"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":[[2024]]},"DOI":"10.1007\/978-3-031-58676-7_7","type":"book-chapter","created":{"date-parts":[[2024,4,26]],"date-time":"2024-04-26T03:02:44Z","timestamp":1714100564000},"page":"82-92","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Evaluation of\u00a0Point Cloud Data Augmentation for\u00a03D-LiDAR Object Detection in\u00a0Autonomous Driving"],"prefix":"10.1007","author":[{"given":"Marta","family":"Martins","sequence":"first","affiliation":[]},{"given":"Iago P.","family":"Gomes","sequence":"additional","affiliation":[]},{"given":"Denis Fernando","family":"Wolf","sequence":"additional","affiliation":[]},{"given":"Cristiano","family":"Premebida","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,4,27]]},"reference":[{"key":"7_CR1","doi-asserted-by":"crossref","unstructured":"Arnold, E., Al-Jarrah, O.Y., Dianati, M., Fallah, S., Oxtoby, D., Mouzakitis, A.: A survey on 3D object detection methods for autonomous driving applications. IEEE Trans. Intell. Transp. Syst. 20(10), 3782\u20133795 (2019)","DOI":"10.1109\/TITS.2019.2892405"},{"key":"7_CR2","unstructured":"Bewley, A., Sun, P., Mensink, T., Anguelov, D., Sminchisescu, C.: Range conditioned dilated convolutions for scale invariant 3D object detection (2020). arXiv preprint arXiv:2005.09927"},{"key":"7_CR3","doi-asserted-by":"crossref","unstructured":"Chai, Y., et al.: To the point: efficient 3D object detection in the range image with graph convolution kernels. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 16,000\u201316,009 (2021)","DOI":"10.1109\/CVPR46437.2021.01574"},{"key":"7_CR4","doi-asserted-by":"crossref","unstructured":"Chen, L., et al.: Deep neural network based vehicle and pedestrian detection for autonomous driving: a survey. IEEE Trans. Intell. Transp. Syst. 22(6), 3234\u20133246 (2021)","DOI":"10.1109\/TITS.2020.2993926"},{"key":"7_CR5","doi-asserted-by":"crossref","unstructured":"Chen, Y., Liu, S., Shen, X., Jia, J.: Fast point R-CNN. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 9775\u20139784 (2019)","DOI":"10.1109\/ICCV.2019.00987"},{"key":"7_CR6","doi-asserted-by":"crossref","unstructured":"Choi, J., Song, Y., Kwak, N.: Part-aware data augmentation for 3D object detection in point cloud. In: 2021 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS) (2021)","DOI":"10.1109\/IROS51168.2021.9635887"},{"key":"7_CR7","doi-asserted-by":"crossref","unstructured":"Fan, L., Xiong, X., Wang, F., Wang, N., Zhang, Z.: RangeDet: in defense of range view for lidar-based 3d object detection. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 2918\u20132927 (2021)","DOI":"10.1109\/ICCV48922.2021.00291"},{"key":"7_CR8","doi-asserted-by":"crossref","unstructured":"Geiger, A., Lenz, P., Stiller, C., Urtasun, R.: Vision meets robotics: the KITTI dataset. Int. J. Robot. Res. 32(11), 1231\u20131237 (2013)","DOI":"10.1177\/0278364913491297"},{"key":"7_CR9","unstructured":"Hahner, M., Dai, D., Liniger, A., Van\u00a0Gool, L.: Quantifying data augmentation for lidar based 3D object detection (2020). arXiv preprint arXiv:2004.01643"},{"key":"7_CR10","doi-asserted-by":"crossref","unstructured":"He, C., Zeng, H., Huang, J., Hua, X.S., Zhang, L.: Structure aware single-stage 3D object detection from point cloud. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (2020)","DOI":"10.1109\/CVPR42600.2020.01189"},{"key":"7_CR11","doi-asserted-by":"publisher","first-page":"1066","DOI":"10.1016\/j.procs.2022.01.135","volume":"199","author":"P Jiang","year":"2022","unstructured":"Jiang, P., Ergu, D., Liu, F., Cai, Y., Ma, B.: A review of yolo algorithm developments. Procedia Comput. Sci. 199, 1066\u20131073 (2022)","journal-title":"Procedia Comput. Sci."},{"key":"7_CR12","doi-asserted-by":"crossref","unstructured":"Kim, S., Lee, S., Hwang, D., Lee, J., Hwang, S.J., Kim, H.J.: Point cloud augmentation with weighted local transformations. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision (ICCV) (2021)","DOI":"10.1109\/ICCV48922.2021.00059"},{"key":"7_CR13","doi-asserted-by":"crossref","unstructured":"Lang, A.H., Vora, S., Caesar, H., Zhou, L., Yang, J., Beijbom, O.: PointPillars: fast encoders for object detection from point clouds. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (2019)","DOI":"10.1109\/CVPR.2019.01298"},{"key":"7_CR14","doi-asserted-by":"crossref","unstructured":"Li, R., Li, X., Heng, P.A., Fu, C.W.: PointAugment: an auto-augmentation framework for point cloud classification. In: 2020 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2020)","DOI":"10.1109\/CVPR42600.2020.00641"},{"key":"7_CR15","doi-asserted-by":"crossref","unstructured":"Li, Z.: Lidar-based 3D object detection for autonomous driving. In: 2022 International Conference on Image Processing, Computer Vision and Machine Learning (ICICML) (2022)","DOI":"10.1109\/ICICML57342.2022.10009752"},{"key":"7_CR16","doi-asserted-by":"crossref","unstructured":"Lim, B.S., Keoh, S.L., Thing, V.L.L.: Autonomous vehicle ultrasonic sensor vulnerability and impact assessment. In: 2018 IEEE 4th World Forum on Internet of Things (WF-IoT) (2018)","DOI":"10.1109\/WF-IoT.2018.8355132"},{"key":"7_CR17","unstructured":"Mao, J., Shi, S., Wang, X., Li, H.: 3D object detection for autonomous driving: A review and new outlooks (2022). arXiv preprint arXiv:2206.09474"},{"key":"7_CR18","unstructured":"Mao, J., Shi, S., Wang, X., Li, H.: 3D object detection for autonomous driving: A review and new outlooks (2022). arXiv preprint arXiv:2206.09474"},{"key":"7_CR19","volume-title":"Autonomous Driving","author":"M Maurer","year":"2016","unstructured":"Maurer, M., Gerdes, J., Lenz, B., Winner, H.: Autonomous Driving. Technical, Legal and Social Aspects (2016)"},{"key":"7_CR20","doi-asserted-by":"crossref","unstructured":"Mousavian, A., Anguelov, D., Flynn, J., Kosecka, J.: 3D bounding box estimation using deep learning and geometry. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2017)","DOI":"10.1109\/CVPR.2017.597"},{"key":"7_CR21","unstructured":"Qi, C.R., Yi, L., Su, H., Guibas, L.J.: PointNet++: deep hierarchical feature learning on point sets in a metric space. In: Advances in Neural Information Processing Systems (2017)"},{"key":"7_CR22","unstructured":"Russell, S.J.: Artificial intelligence a modern approach. Pearson Education, Inc. (2010)"},{"key":"7_CR23","doi-asserted-by":"publisher","DOI":"10.1109\/MCG.2004.1","author":"M Sainz","year":"2004","unstructured":"Sainz, M., Pajarola, R., Mercade, A., Susin, A.: A simple approach for point-based object capturing and rendering. IEEE Comput. Graphics Appl. (2004). https:\/\/doi.org\/10.1109\/MCG.2004.1","journal-title":"IEEE Comput. Graphics Appl."},{"key":"7_CR24","doi-asserted-by":"crossref","unstructured":"Sheshappanavar, S.V., Singh, V.V., Kambhamettu, C.: PatchAugment: local neighborhood augmentation in point cloud classification. In: 2021 IEEE\/CVF International Conference on Computer Vision Workshops (ICCVW) (2021)","DOI":"10.1109\/ICCVW54120.2021.00240"},{"key":"7_CR25","doi-asserted-by":"crossref","unstructured":"Shi, S., Wang, X., Li, H.: PointRCNN: 3D object proposal generation and detection from point cloud. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 770\u2013779 (2019)","DOI":"10.1109\/CVPR.2019.00086"},{"key":"7_CR26","doi-asserted-by":"crossref","unstructured":"Shi, W., Rajkumar, R.: Point-GNN: graph neural network for 3D object detection in a point cloud. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 1711\u20131719 (2020)","DOI":"10.1109\/CVPR42600.2020.00178"},{"key":"7_CR27","doi-asserted-by":"crossref","unstructured":"Wang, Y., et al.: Multi-modal 3D object detection in autonomous driving: a survey. Int. J. Comput. Vis. 1(31), 2122\u20132152 (2023)","DOI":"10.1007\/s11263-023-01784-z"},{"key":"7_CR28","doi-asserted-by":"crossref","unstructured":"Yan, Y., Mao, Y., Li, B.: SECOND: sparsely embedded convolutional detection. Sensors 18(10), 3337 (2018)","DOI":"10.3390\/s18103337"},{"key":"7_CR29","doi-asserted-by":"crossref","unstructured":"Zhou, Y., Tuzel, O.: VoxelNet: end-to-end learning for point cloud based 3D object detection. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 4490\u20134499 (2018)","DOI":"10.1109\/CVPR.2018.00472"}],"container-title":["Lecture Notes in Networks and Systems","Robot 2023: Sixth Iberian Robotics Conference"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-58676-7_7","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,9]],"date-time":"2026-02-09T18:03:01Z","timestamp":1770660181000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-58676-7_7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031586750","9783031586767"],"references-count":29,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-58676-7_7","relation":{},"ISSN":["2367-3370","2367-3389"],"issn-type":[{"value":"2367-3370","type":"print"},{"value":"2367-3389","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"27 April 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ROBOT","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Iberian Robotics conference","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Coimbra","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Portugal","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 November 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24 November 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"robot2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.iberianroboticsconf.eu\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}