{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T19:48:24Z","timestamp":1776196104321,"version":"3.50.1"},"publisher-location":"Cham","reference-count":55,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031726699","type":"print"},{"value":"9783031726705","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,9,30]],"date-time":"2024-09-30T00:00:00Z","timestamp":1727654400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,9,30]],"date-time":"2024-09-30T00:00:00Z","timestamp":1727654400000},"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":[[2025]]},"DOI":"10.1007\/978-3-031-72670-5_15","type":"book-chapter","created":{"date-parts":[[2024,9,29]],"date-time":"2024-09-29T07:01:50Z","timestamp":1727593310000},"page":"259-276","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Shape-Guided Configuration-Aware Learning for\u00a0Endoscopic-Image-Based Pose Estimation of\u00a0Flexible Robotic Instruments"],"prefix":"10.1007","author":[{"given":"Yiyao","family":"Ma","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kai","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hon-Sing","family":"Tong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ruofeng","family":"Wei","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yui-Lun","family":"Ng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ka-Wai","family":"Kwok","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qi","family":"Dou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,9,30]]},"reference":[{"key":"15_CR1","doi-asserted-by":"crossref","unstructured":"Afham, M., Dissanayake, I., Dissanayake, D., Dharmasiri, A., Thilakarathna, K., Rodrigo, R.: Crosspoint: self-supervised cross-modal contrastive learning for 3d point cloud understanding. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 9902\u20139912 (2022)","DOI":"10.1109\/CVPR52688.2022.00967"},{"key":"15_CR2","doi-asserted-by":"crossref","unstructured":"Arsomngern, P., Nutanong, S., Suwajanakorn, S.: Learning geometric-aware properties in 2D representation using lightweight cad models, or zero real 3D pairs. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 21371\u201321381 (2023)","DOI":"10.1109\/CVPR52729.2023.02047"},{"issue":"1","key":"15_CR3","doi-asserted-by":"publisher","first-page":"44","DOI":"10.1039\/D2SM00914E","volume":"19","author":"T Baaij","year":"2023","unstructured":"Baaij, T., et al.: Learning 3D shape proprioception for continuum soft robots with multiple magnetic sensors. Soft Matter 19(1), 44\u201356 (2023)","journal-title":"Soft Matter"},{"key":"15_CR4","doi-asserted-by":"crossref","unstructured":"Bili\u0107, I., Mari\u0107, F., Markovi\u0107, I., Petrovi\u0107, I.: A distance-geometric method for recovering robot joint angles from an RGB image. arXiv preprint arXiv:2301.02051 (2023)","DOI":"10.1016\/j.ifacol.2023.10.1696"},{"key":"15_CR5","doi-asserted-by":"crossref","unstructured":"Cartucho, J., Wang, C., Huang, B., S.\u00a0Elson, D., Darzi, A., Giannarou, S.: An enhanced marker pattern that achieves improved accuracy in surgical tool tracking. Comput. Meth. Biomech. Biomed. Eng. Imaging Visual. 10(4), 400\u2013408 (2022)","DOI":"10.1080\/21681163.2021.1997647"},{"issue":"6","key":"15_CR6","doi-asserted-by":"publisher","first-page":"1900086","DOI":"10.1002\/aisy.201900086","volume":"2","author":"C Chautems","year":"2020","unstructured":"Chautems, C., Tonazzini, A., Boehler, Q., Jeong, S.H., Floreano, D., Nelson, B.J.: Magnetic continuum device with variable stiffness for minimally invasive surgery. Adv. Intell. Syst. 2(6), 1900086 (2020)","journal-title":"Adv. Intell. Syst."},{"issue":"6","key":"15_CR7","doi-asserted-by":"publisher","first-page":"1900171","DOI":"10.1002\/aisy.201900171","volume":"2","author":"K Chin","year":"2020","unstructured":"Chin, K., Hellebrekers, T., Majidi, C.: Machine learning for soft robotic sensing and control. Ad. Intell. Syst. 2(6), 1900171 (2020)","journal-title":"Ad. Intell. Syst."},{"issue":"6","key":"15_CR8","doi-asserted-by":"publisher","first-page":"2280","DOI":"10.1016\/j.patcog.2014.01.005","volume":"47","author":"S Garrido-Jurado","year":"2014","unstructured":"Garrido-Jurado, S., Mu\u00f1oz-Salinas, R., Madrid-Cuevas, F.J., Mar\u00edn-Jim\u00e9nez, M.J.: Automatic generation and detection of highly reliable fiducial markers under occlusion. Pattern Recogn. 47(6), 2280\u20132292 (2014)","journal-title":"Pattern Recogn."},{"issue":"4","key":"15_CR9","doi-asserted-by":"publisher","first-page":"589","DOI":"10.1038\/s41551-021-00767-0","volume":"7","author":"G Gu","year":"2023","unstructured":"Gu, G., et al.: A soft neuroprosthetic hand providing simultaneous myoelectric control and tactile feedback. Nat. Biomed. Eng. 7(4), 589\u2013598 (2023)","journal-title":"Nat. Biomed. Eng."},{"issue":"48","key":"15_CR10","doi-asserted-by":"publisher","first-page":"2103320","DOI":"10.1002\/adma.202103320","volume":"33","author":"KH Ha","year":"2021","unstructured":"Ha, K.H., et al.: Highly sensitive capacitive pressure sensors over a wide pressure range enabled by the hybrid responses of a highly porous nanocomposite. Adv. Mater. 33(48), 2103320 (2021)","journal-title":"Adv. Mater."},{"key":"15_CR11","doi-asserted-by":"crossref","unstructured":"He, Y., et al.: Stretchable optical fibre sensor for soft surgical robot shape reconstruction. Optica Applicata 51(4) (2021)","DOI":"10.37190\/oa210410"},{"key":"15_CR12","unstructured":"Heindl, C., Zambal, S., Ponitz, T., Pichler, A., Scharinger, J.: 3D robot pose estimation from 2d images. arXiv preprint arXiv:1902.04987 (2019)"},{"key":"15_CR13","doi-asserted-by":"crossref","unstructured":"Jing, L., Vahdani, E., Tan, J., Tian, Y.: Cross-modal center loss for 3D cross-modal retrieval. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 3142\u20133151 (2021)","DOI":"10.1109\/CVPR46437.2021.00316"},{"key":"15_CR14","doi-asserted-by":"crossref","unstructured":"Katzschmann, R.K., et al.: Dynamically closed-loop controlled soft robotic arm using a reduced order finite element model with state observer. In: 2019 2nd IEEE International Conference on Soft Robotics (RoboSoft), pp. 717\u2013724. IEEE (2019)","DOI":"10.1109\/ROBOSOFT.2019.8722804"},{"issue":"1","key":"15_CR15","doi-asserted-by":"publisher","first-page":"95","DOI":"10.1111\/j.2517-6161.1977.tb01610.x","volume":"39","author":"C Khatri","year":"1977","unstructured":"Khatri, C., Mardia, K.V.: The von mises-fisher matrix distribution in orientation statistics. J. R. Stat. Soc. Ser. B Stat Methodol. 39(1), 95\u2013106 (1977)","journal-title":"J. R. Stat. Soc. Ser. B Stat Methodol."},{"key":"15_CR16","doi-asserted-by":"crossref","unstructured":"Kim, S.Y., et al.: Sustainable manufacturing of sensors onto soft systems using self-coagulating conductive pickering emulsions. Sci. Robot. 5(39), eaay3604 (2020)","DOI":"10.1126\/scirobotics.aay3604"},{"key":"15_CR17","doi-asserted-by":"crossref","unstructured":"Lambrecht, J., Grosenick, P., Meusel, M.: Optimizing keypoint-based single-shot camera-to-robot pose estimation through shape segmentation. In: 2021 IEEE International Conference on Robotics and Automation (ICRA), pp. 13843\u201313849. IEEE (2021)","DOI":"10.1109\/ICRA48506.2021.9561670"},{"key":"15_CR18","doi-asserted-by":"crossref","unstructured":"Lee, T.E., et al.: Camera-to-robot pose estimation from a single image. In: 2020 IEEE International Conference on Robotics and Automation (ICRA), pp. 9426\u20139432. IEEE (2020)","DOI":"10.1109\/ICRA40945.2020.9196596"},{"issue":"2","key":"15_CR19","doi-asserted-by":"publisher","first-page":"155","DOI":"10.1007\/s11263-008-0152-6","volume":"81","author":"V Lepetit","year":"2009","unstructured":"Lepetit, V., Moreno-Noguer, F., Fua, P.: EPNP: An accurate o (n) solution to the PNP problem. Int. J. Comput. Vision 81(2), 155\u2013166 (2009)","journal-title":"Int. J. Comput. Vision"},{"key":"15_CR20","doi-asserted-by":"crossref","unstructured":"Li, S., Hao, G.: Current trends and prospects in compliant continuum robots: a survey. In: Actuators, vol.\u00a010, p.\u00a0145. MDPI (2021)","DOI":"10.3390\/act10070145"},{"key":"15_CR21","doi-asserted-by":"crossref","unstructured":"Lin, M.X., et al.: Single image 3D shape retrieval via cross-modal instance and category contrastive learning. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 11405\u201311415 (2021)","DOI":"10.1109\/ICCV48922.2021.01121"},{"issue":"3","key":"15_CR22","doi-asserted-by":"publisher","first-page":"591","DOI":"10.1089\/soro.2020.0024","volume":"9","author":"JY Loo","year":"2022","unstructured":"Loo, J.Y., Ding, Z.Y., Baskaran, V.M., Nurzaman, S.G., Tan, C.P.: Robust multimodal indirect sensing for soft robots via neural network-aided filter-based estimation. Soft Rob. 9(3), 591\u2013612 (2022)","journal-title":"Soft Rob."},{"key":"15_CR23","doi-asserted-by":"crossref","unstructured":"Lu, J., Liu, F., Girerd, C., Yip, M.: Image-based pose estimation and shape reconstruction for robot manipulators and soft, continuum robots via differentiable rendering. In: ICRA 2023-IEEE International Conference on Robotics and Automation (2023)","DOI":"10.1109\/ICRA48891.2023.10161066"},{"key":"15_CR24","doi-asserted-by":"crossref","unstructured":"Lu, J., Richter, F., Lin, S., Yip, M.C.: Tracking snake-like robots in the wild using only a single camera. arXiv preprint arXiv:2309.15700 (2023)","DOI":"10.1109\/ICRA57147.2024.10611438"},{"issue":"2","key":"15_CR25","doi-asserted-by":"publisher","first-page":"4622","DOI":"10.1109\/LRA.2022.3151981","volume":"7","author":"J Lu","year":"2022","unstructured":"Lu, J., Richter, F., Yip, M.C.: Pose estimation for robot manipulators via keypoint optimization and sim-to-real transfer. IEEE Robot. Autom. Lett. 7(2), 4622\u20134629 (2022)","journal-title":"IEEE Robot. Autom. Lett."},{"key":"15_CR26","doi-asserted-by":"publisher","DOI":"10.3389\/frobt.2021.702566","volume":"8","author":"LO Mair","year":"2021","unstructured":"Mair, L.O., et al.: Soft capsule magnetic millirobots for region-specific drug delivery in the central nervous system. Front. Robot. AI 8, 702566 (2021)","journal-title":"Front. Robot. AI"},{"key":"15_CR27","doi-asserted-by":"crossref","unstructured":"Monet, F., et al.: High-resolution optical fiber shape sensing of continuum robots: a comparative study. In: 2020 IEEE International Conference on Robotics and Automation (ICRA), pp. 8877\u20138883. IEEE (2020)","DOI":"10.1109\/ICRA40945.2020.9197454"},{"issue":"4","key":"15_CR28","doi-asserted-by":"publisher","first-page":"5621","DOI":"10.1109\/LRA.2020.3008120","volume":"5","author":"SE Navarro","year":"2020","unstructured":"Navarro, S.E.: A model-based sensor fusion approach for force and shape estimation in soft robotics. IEEE Robot. Autom. Lett. 5(4), 5621\u20135628 (2020)","journal-title":"IEEE Robot. Autom. Lett."},{"key":"15_CR29","doi-asserted-by":"crossref","unstructured":"Ozel, S., et al.: A composite soft bending actuation module with integrated curvature sensing. In: 2016 IEEE International Conference on Robotics and Automation (ICRA), pp. 4963\u20134968. IEEE (2016)","DOI":"10.1109\/ICRA.2016.7487703"},{"issue":"2","key":"15_CR30","doi-asserted-by":"publisher","first-page":"214","DOI":"10.1111\/j.2517-6161.1986.tb01404.x","volume":"48","author":"MJ Prentice","year":"1986","unstructured":"Prentice, M.J.: Orientation statistics without parametric assumptions. J. R. Stat. Soc. Ser. B Stat Methodol. 48(2), 214\u2013222 (1986)","journal-title":"J. R. Stat. Soc. Ser. B Stat Methodol."},{"key":"15_CR31","unstructured":"Qi, C.R., Su, H., Mo, K., Guibas, L.J.: PointNet: Deep learning on point sets for 3D classification and segmentation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 652\u2013660 (2017)"},{"key":"15_CR32","doi-asserted-by":"crossref","unstructured":"Ranftl, R., Bochkovskiy, A., Koltun, V.: Vision transformers for dense prediction. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 12179\u201312188 (2021)","DOI":"10.1109\/ICCV48922.2021.01196"},{"issue":"1","key":"15_CR33","doi-asserted-by":"publisher","first-page":"187","DOI":"10.1109\/TRO.2015.2507160","volume":"32","author":"T Ranzani","year":"2016","unstructured":"Ranzani, T., Cianchetti, M., Gerboni, G., De Falco, I., Menciassi, A.: A soft modular manipulator for minimally invasive surgery: design and characterization of a single module. IEEE Trans. Rob. 32(1), 187\u2013200 (2016)","journal-title":"IEEE Trans. Rob."},{"key":"15_CR34","doi-asserted-by":"publisher","first-page":"30","DOI":"10.3389\/frobt.2019.00030","volume":"6","author":"B Shih","year":"2019","unstructured":"Shih, B., et al.: Design considerations for 3D printed, soft, multimaterial resistive sensors for soft robotics. Front. Robot. AI 6, 30 (2019)","journal-title":"Front. Robot. AI"},{"key":"15_CR35","doi-asserted-by":"crossref","unstructured":"Souipas, S., Nguyen, A., Laws, S.G., Davies, B.L., Baena, F.R.: SIMPS-Net: simultaneous pose & segmentation network of surgical tools. IEEE Trans. Med. Robot. Bionics (2023)","DOI":"10.1109\/TMRB.2023.3291022"},{"issue":"4","key":"15_CR36","doi-asserted-by":"publisher","first-page":"11244","DOI":"10.1109\/LRA.2022.3199034","volume":"7","author":"K Tanaka","year":"2022","unstructured":"Tanaka, K., Minami, Y., Tokudome, Y., Inoue, K., Kuniyoshi, Y., Nakajima, K.: Continuum-body-pose estimation from partial sensor information using recurrent neural networks. IEEE Robot. Autom. Lett. 7(4), 11244\u201311251 (2022)","journal-title":"IEEE Robot. Autom. Lett."},{"key":"15_CR37","doi-asserted-by":"crossref","unstructured":"Teyssier, M., Parilusyan, B., Roudaut, A., Steimle, J.: Human-like artificial skin sensor for physical human-robot interaction. In: 2021 IEEE International Conference on Robotics and Automation (ICRA), pp. 3626\u20133633. IEEE (2021)","DOI":"10.1109\/ICRA48506.2021.9561152"},{"key":"15_CR38","doi-asserted-by":"crossref","unstructured":"Thuruthel, T.G., Shih, B., Laschi, C., Tolley, M.T.: Soft robot perception using embedded soft sensors and recurrent neural networks. Sci. Robot. 4(26), eaav1488 (2019)","DOI":"10.1126\/scirobotics.aav1488"},{"key":"15_CR39","doi-asserted-by":"crossref","unstructured":"Tian, Y., Zhang, J., Yin, Z., Dong, H.: Robot structure prior guided temporal attention for camera-to-robot pose estimation from image sequence. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 8917\u20138926 (2023)","DOI":"10.1109\/CVPR52729.2023.00861"},{"key":"15_CR40","doi-asserted-by":"crossref","unstructured":"Toshimitsu, Y., Wong, K.W., Buchner, T., Katzschmann, R.: Sopra: fabrication & dynamical modeling of a scalable soft continuum robotic arm with integrated proprioceptive sensing. In: 2021 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 653\u2013660. IEEE (2021)","DOI":"10.1109\/IROS51168.2021.9636539"},{"issue":"2","key":"15_CR41","doi-asserted-by":"publisher","first-page":"3299","DOI":"10.1109\/LRA.2020.2976320","volume":"5","author":"RL Truby","year":"2020","unstructured":"Truby, R.L., Della Santina, C., Rus, D.: Distributed proprioception of 3D configuration in soft, sensorized robots via deep learning. IEEE Robot. Autom. Lett. 5(2), 3299\u20133306 (2020)","journal-title":"IEEE Robot. Autom. Lett."},{"key":"15_CR42","unstructured":"Valassakis, E., Dreczkowski, K., Johns, E.: Learning eye-in-hand camera calibration from a single image. In: Conference on Robot Learning, pp. 1336\u20131346. PMLR (2022)"},{"key":"15_CR43","doi-asserted-by":"crossref","unstructured":"Wang, Y., Chen, X., Cao, L., Huang, W., Sun, F., Wang, Y.: Multimodal token fusion for vision transformers. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 12186\u201312195 (2022)","DOI":"10.1109\/CVPR52688.2022.01187"},{"key":"15_CR44","doi-asserted-by":"crossref","unstructured":"Wang, Y., Ye, T., Cao, L., Huang, W., Sun, F., He, F., Tao, D.: Bridged transformer for vision and point cloud 3D object detection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 12114\u201312123 (2022)","DOI":"10.1109\/CVPR52688.2022.01180"},{"issue":"13","key":"15_CR45","doi-asserted-by":"publisher","first-page":"1661","DOI":"10.1177\/0278364910368147","volume":"29","author":"RJ Webster III","year":"2010","unstructured":"Webster, R.J., III., Jones, B.A.: Design and kinematic modeling of constant curvature continuum robots: a review. Int. J. Robot. Res. 29(13), 1661\u20131683 (2010)","journal-title":"Int. J. Robot. Res."},{"key":"15_CR46","doi-asserted-by":"crossref","unstructured":"Xu, H., Runciman, M., Cartucho, J., Xu, C., Giannarou, S.: Graph-based pose estimation of texture-less surgical tools for autonomous robot control. In: 2023 IEEE International Conference on Robotics and Automation (ICRA), pp. 2731\u20132737. IEEE (2023)","DOI":"10.1109\/ICRA48891.2023.10160287"},{"key":"15_CR47","doi-asserted-by":"crossref","unstructured":"Xu, P., Zhu, X., Clifton, D.A.: Multimodal learning with transformers: a survey. IEEE Trans. Pattern Anal. Mach. Intell. (2023)","DOI":"10.1109\/TPAMI.2023.3275156"},{"key":"15_CR48","unstructured":"Yang, J., Gao, M., Li, Z., Gao, S., Wang, F., Zheng, F.: Track anything: segment anything meets videos. arXiv preprint arXiv:2304.11968 (2023)"},{"key":"15_CR49","doi-asserted-by":"crossref","unstructured":"Yin, Y., Cai, Y., Wang, H., Chen, B.: Fishermatch: semi-supervised rotation regression via entropy-based filtering. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 11164\u201311173 (2022)","DOI":"10.1109\/CVPR52688.2022.01088"},{"key":"15_CR50","doi-asserted-by":"crossref","unstructured":"Yoshimura, M., Marinho, M.M., Harada, K., Mitsuishi, M.: Single-shot pose estimation of surgical robot instruments\u2019 shafts from monocular endoscopic images. In: 2020 IEEE International Conference on Robotics and Automation (ICRA), pp. 9960\u20139966. IEEE (2020)","DOI":"10.1109\/ICRA40945.2020.9196779"},{"key":"15_CR51","doi-asserted-by":"publisher","first-page":"921","DOI":"10.1007\/s11548-017-1558-9","volume":"12","author":"L Zhang","year":"2017","unstructured":"Zhang, L., Ye, M., Chan, P.L., Yang, G.Z.: Real-time surgical tool tracking and pose estimation using a hybrid cylindrical marker. Int. J. Comput. Assist. Radiol. Surg. 12, 921\u2013930 (2017)","journal-title":"Int. J. Comput. Assist. Radiol. Surg."},{"issue":"3","key":"15_CR52","doi-asserted-by":"publisher","first-page":"236","DOI":"10.1145\/357994.358023","volume":"27","author":"TY Zhang","year":"1984","unstructured":"Zhang, T.Y., Suen, C.Y.: A fast parallel algorithm for thinning digital patterns. Commun. ACM 27(3), 236\u2013239 (1984)","journal-title":"Commun. ACM"},{"key":"15_CR53","doi-asserted-by":"crossref","unstructured":"Zhang, Z., Wang, X., Wang, S., Meng, D., Liang, B.: Shape detection and reconstruction of soft robotic arm based on fiber BRAGG grating sensor array. In: 2018 IEEE International Conference on Robotics and Biomimetics (ROBIO), pp. 978\u2013983. IEEE (2018)","DOI":"10.1109\/ROBIO.2018.8665266"},{"issue":"2","key":"15_CR54","doi-asserted-by":"publisher","first-page":"28","DOI":"10.1007\/s10846-023-01957-5","volume":"109","author":"X Zhong","year":"2023","unstructured":"Zhong, X., Zhu, W., Liu, W., Yi, J., Liu, C., Wu, Z.: G-SAM: a robust one-shot keypoint detection framework for PNP based robot pose estimation. J. Intell. Robot. Syst. 109(2), 28 (2023)","journal-title":"J. Intell. Robot. Syst."},{"issue":"5","key":"15_CR55","doi-asserted-by":"publisher","first-page":"2100011","DOI":"10.1002\/aisy.202100011","volume":"3","author":"J Zhu","year":"2021","unstructured":"Zhu, J., et al.: Intelligent soft surgical robots for next-generation minimally invasive surgery. Adv. Intell. Syst. 3(5), 2100011 (2021)","journal-title":"Adv. Intell. Syst."}],"container-title":["Lecture Notes in Computer Science","Computer Vision \u2013 ECCV 2024"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-72670-5_15","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,29]],"date-time":"2024-09-29T07:20:40Z","timestamp":1727594440000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-72670-5_15"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,9,30]]},"ISBN":["9783031726699","9783031726705"],"references-count":55,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-72670-5_15","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,9,30]]},"assertion":[{"value":"30 September 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ECCV","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"European Conference on Computer Vision","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Milan","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Italy","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29 September 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4 October 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"eccv2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/eccv2024.ecva.net\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}