{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,3]],"date-time":"2026-03-03T05:21:14Z","timestamp":1772515274118,"version":"3.50.1"},"reference-count":54,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100006579","name":"Ministry of Industry and Information Technology of the People's Republic of China","doi-asserted-by":"publisher","award":["CJ03N20"],"award-info":[{"award-number":["CJ03N20"]}],"id":[{"id":"10.13039\/501100006579","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Intel Serv Robotics"],"published-print":{"date-parts":[[2026,3]]},"DOI":"10.1007\/s11370-026-00694-6","type":"journal-article","created":{"date-parts":[[2026,3,3]],"date-time":"2026-03-03T04:11:39Z","timestamp":1772511099000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Indoor scene neural implicit 3D reconstruction with SO (3)-equivariant network"],"prefix":"10.1007","volume":"19","author":[{"given":"Caiping","family":"Liang","sequence":"first","affiliation":[]},{"given":"Jian","family":"Yuan","sequence":"additional","affiliation":[]},{"given":"Yongjie","family":"Gao","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3235-2022","authenticated-orcid":false,"given":"Wenxu","family":"Niu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2026,3,3]]},"reference":[{"key":"694_CR1","doi-asserted-by":"crossref","unstructured":"Newcombe, R.A., Izadi, S., Hilliges, O., Molyneaux, D., Kim, D., Davison, A.J.,Kohi, P., Shotton, J., Hodges, S., Fitzgibbon, A.: Kinectfusion: Real-time densesurface mapping and tracking. In: 2011 10th IEEE International Symposium on Mixed and Augmented Reality, pp. 127\u2013136 (2011). IEEE","DOI":"10.1109\/ISMAR.2011.6092378"},{"issue":"6","key":"694_CR2","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/2508363.2508374","volume":"32","author":"M Nie\u00dfner","year":"2013","unstructured":"Nie\u00dfner M, Zollh\u00a8ofer M, Izadi S, Stamminger M (2013) Real-time 3d reconstruction at scale using voxel hashing. ACM Transact Graphic (ToG) 32(6):1\u201311","journal-title":"ACM Transact Graphic (ToG)"},{"key":"694_CR3","doi-asserted-by":"crossref","unstructured":"Park, J.J., Florence, P., Straub, J., Newcombe, R., Lovegrove, S.: Deepsdf: Learning continuous signed distance functions for shape representation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp.165\u2013174 (2019)","DOI":"10.1109\/CVPR.2019.00025"},{"key":"694_CR4","doi-asserted-by":"crossref","unstructured":"Mescheder, L., Oechsle, M., Niemeyer, M., Nowozin, S., Geiger, A.: Occupancy networks: Learning 3d reconstruction in function space. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 4460\u20134470 (2019)","DOI":"10.1109\/CVPR.2019.00459"},{"key":"694_CR5","doi-asserted-by":"crossref","unstructured":"Whelan, T., Leutenegger, S., Salas-Moreno, R., Glocker, B., Davison, A.: Elasticfusion: Dense slam without a pose graph. (2015). Robotics: Science and Systems","DOI":"10.15607\/RSS.2015.XI.001"},{"issue":"3","key":"694_CR6","doi-asserted-by":"publisher","first-page":"7075","DOI":"10.1109\/LRA.2022.3181356","volume":"7","author":"Y Yuan","year":"2022","unstructured":"Yuan Y, N\u00a8uchter A (2022) Indirect point cloud registration: aligning distance fields using a pseudo third point set. IEEE Robot Autom Lett 7(3):7075\u20137082","journal-title":"IEEE Robot Autom Lett"},{"key":"694_CR7","doi-asserted-by":"crossref","unstructured":"Chen, Z., Tagliasacchi, A., Zhang, H.: Bsp-net: Generating compact meshes via binary space partitioning. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 45\u201354 (2020)","DOI":"10.1109\/CVPR42600.2020.00012"},{"key":"694_CR8","doi-asserted-by":"crossref","unstructured":"Chibane, J., Alldieck, T., Pons-Moll, G.: Implicit functions in feature space for 3d shape reconstruction and completion. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 6970\u20136981 (2020)","DOI":"10.1109\/CVPR42600.2020.00700"},{"key":"694_CR9","doi-asserted-by":"crossref","unstructured":"Genova, K., Cole, F., Sud, A., Sarna, A., Funkhouser, T.: Local deep implicit functions for 3d shape. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 4857\u20134866 (2020)","DOI":"10.1109\/CVPR42600.2020.00491"},{"key":"694_CR10","doi-asserted-by":"crossref","unstructured":"Genova, K., Cole, F., Vlasic, D., Sarna, A., Freeman, W.T., Funkhouser, T.:Learning shape templates with structured implicit functions. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 7154\u20137164 (2019)","DOI":"10.1109\/ICCV.2019.00725"},{"key":"694_CR11","doi-asserted-by":"crossref","unstructured":"Oechsle, M., Mescheder, L., Niemeyer, M., Strauss, T., Geiger, A.: Texture fields: Learning texture representations in function space. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 4531\u20134540 (2019)","DOI":"10.1109\/ICCV.2019.00463"},{"key":"694_CR12","doi-asserted-by":"crossref","unstructured":"Sucar, E., Liu, S., Ortiz, J., Davison, A.J.: imap: Implicit mapping and positioning in real-time. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 6229\u20136238 (2021)","DOI":"10.1109\/ICCV48922.2021.00617"},{"key":"694_CR13","doi-asserted-by":"crossref","unstructured":"Zhu, Z., Peng, S., Larsson, V., Xu, W., Bao, H., Cui, Z., Oswald, M.R., Pollefeys,M.: Nice-slam: Neural implicit scalable encoding for slam. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp.12786\u201312796 (2022)","DOI":"10.1109\/CVPR52688.2022.01245"},{"key":"694_CR14","doi-asserted-by":"crossref","unstructured":"Huang, J., Huang, S.-S., Song, H., Hu, S.-M.: Di-fusion: Online implicit 3d reconstruction with deep priors. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 8932\u20138941 (2021)","DOI":"10.1109\/CVPR46437.2021.00882"},{"key":"694_CR15","doi-asserted-by":"crossref","unstructured":"Chen, Y., Liu, S., Wang, X.: Learning continuous image representation with local implicit image function. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 8628\u20138638 (2021)","DOI":"10.1109\/CVPR46437.2021.00852"},{"key":"694_CR16","doi-asserted-by":"crossref","unstructured":"Deng, C., Litany, O., Duan, Y., Poulenard, A., Tagliasacchi, A., Guibas, L.J.: Vector neurons: A general framework for so (3)-equivariant networks. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 12200\u201312209 (2021)","DOI":"10.1109\/ICCV48922.2021.01198"},{"key":"694_CR17","doi-asserted-by":"crossref","unstructured":"Chang, A., Dai, A., Funkhouser, T., Halber, M., Niessner, M., Savva, M., Song,S., Zeng, A., Zhang, Y.: Matterport3d: Learning from rgb-d data in indoor environments. arXiv preprint arXiv:1709.06158 (2017)","DOI":"10.1109\/3DV.2017.00081"},{"key":"694_CR18","doi-asserted-by":"crossref","unstructured":"Handa, A., Whelan, T., McDonald, J., Davison, A.J.: A benchmark for rgb-d visual odometry, 3d reconstruction and slam. In: 2014 IEEE International Conference on Robotics and Automation (ICRA), pp. 1524\u20131531 (2014). IEEE","DOI":"10.1109\/ICRA.2014.6907054"},{"key":"694_CR19","unstructured":"Straub, J., Whelan, T., Ma, L., Chen, Y., Wijmans, S., et al.: The replica dataset: A digital replica of indoor spaces. arXiv preprint arXiv:1906.05797 (2019)"},{"key":"694_CR20","doi-asserted-by":"crossref","unstructured":"Fan, H., Su, H., Guibas, L.J.: A point set generation network for 3d object reconstruction from a single image. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 605\u2013613 (2017)","DOI":"10.1109\/CVPR.2017.264"},{"key":"694_CR21","doi-asserted-by":"crossref","unstructured":"Lin, C.-H., Kong, C., Lucey, S.: Learning efficient point cloud generation for dense 3d object reconstruction. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 32 (2018)","DOI":"10.1609\/aaai.v32i1.12278"},{"key":"694_CR22","doi-asserted-by":"crossref","unstructured":"Choy, C.B., Xu, D., Gwak, J., Chen, K., Savarese, S.: 3d-r2n2: A unified approach for single and multi-view 3d object reconstruction. In: Computer Vision\u2013ECCV 2016: 14th European Conference, Amsterdam, The Netherlands, October 11\u201314,2016, Proceedings, Part VIII 14, pp. 628\u2013644 (2016). Springer","DOI":"10.1007\/978-3-319-46484-8_38"},{"key":"694_CR23","doi-asserted-by":"crossref","unstructured":"Xie, H., Yao, H., Sun, X., Zhou, S., Zhang, S.: Pix2vox: Context-aware 3d reconstruction from single and multi-view images. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 2690\u20132698 (2019)","DOI":"10.1109\/ICCV.2019.00278"},{"key":"694_CR24","doi-asserted-by":"crossref","unstructured":"Li, H., Ye, W., Zhang, G., Zhang, S., Bao, H.: Saliency guided subdivision for single-view mesh reconstruction. In: 2020 International Conference on 3D Vision (3DV), pp. 1098\u20131107 (2020). IEEE","DOI":"10.1109\/3DV50981.2020.00120"},{"key":"694_CR25","doi-asserted-by":"crossref","unstructured":"Wang, N., Zhang, Y., Li, Z., Fu, Y., Liu, W., Jiang, Y.-G.: Pixel2mesh: Generating 3d mesh models from single rgb images. In: Proceedings of the European Conference on Computer Vision (ECCV), pp. 52\u201367 (2018)","DOI":"10.1007\/978-3-030-01252-6_4"},{"key":"694_CR26","doi-asserted-by":"crossref","unstructured":"Kato, H., Ushiku, Y., Harada, T.: Neural 3d mesh renderer. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3907\u20133916 (2018)","DOI":"10.1109\/CVPR.2018.00411"},{"key":"694_CR27","doi-asserted-by":"crossref","unstructured":"Lorensen, W.E., Cline, H.E.: Marching cubes: A high resolution 3d surface construction algorithm. In: Seminal Graphics: Pioneering Efforts that Shaped the Field, pp. 347\u2013353 (1998)","DOI":"10.1145\/280811.281026"},{"key":"694_CR28","doi-asserted-by":"crossref","unstructured":"Jiang, C., Sud, A., Makadia, A., Huang, J., Nie\u00dfner, M., Funkhouser, T., et al.:Local implicit grid representations for 3d scenes. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 6001\u20136010 (2020)","DOI":"10.1109\/CVPR42600.2020.00604"},{"key":"694_CR29","doi-asserted-by":"crossref","unstructured":"Peng, S., Niemeyer, M., Mescheder, L., Pollefeys, M., Geiger, A.: Convolutional occupancy networks. In: Computer Vision\u2013ECCV 2020: 16th European Conference,Glasgow, UK, August 23\u201328, 2020, Proceedings, Part III 16, pp. 523\u2013540 (2020).Springer","DOI":"10.1007\/978-3-030-58580-8_31"},{"key":"694_CR30","doi-asserted-by":"crossref","unstructured":"Azinovi\u00b4c, D., Martin-Brualla, R., Goldman, D.B., Nie\u00dfner, M., Thies, J.: Neural rgb-d surface reconstruction. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 6290\u20136301 (2022)","DOI":"10.1109\/CVPR52688.2022.00619"},{"key":"694_CR31","doi-asserted-by":"crossref","unstructured":"Weder, S., Schonberger, J.L., Pollefeys, M., Oswald, M.R.: Neuralfusion: Online depth fusion in latent space. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 3162\u20133172 (2021)","DOI":"10.1109\/CVPR46437.2021.00318"},{"key":"694_CR32","unstructured":"Liu, L., Gu, J., Zaw Lin, K., Chua, T.-S., Theobalt, C.: Neural sparse voxel fields.Advances in Neural Information Processing Systems 33, 15651\u201315663 (2020)"},{"key":"694_CR33","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":"694_CR34","doi-asserted-by":"crossref","unstructured":"Zhang, J., Shi, J., Zou, D., Shu, X., Bai, S., Lu, J., Zhu, H., Ni, J., Sun, Y.: Epmnet: Efficient feature extraction, point-pair feature matching for robust 6-d pose estimation. IEEE Transactions on Multimedia (2023)","DOI":"10.1109\/TMM.2023.3330116"},{"key":"694_CR35","unstructured":"Thomas, N., Smidt, T., Kearnes, S., Yang, L., Li, L., Kohlhoff, K., Riley, P.:Tensor field networks: Rotation-and translation-equivariant neural networks for3d point clouds. arXiv preprint arXiv:1802.08219 (2018)"},{"key":"694_CR36","unstructured":"Kondor, R., Lin, Z., Trivedi, S.: Clebsch\u2013gordan nets: a fully fourier space spherical convolutional neural network. Advances in Neural Information Processing Systems 31 (2018)"},{"key":"694_CR37","first-page":"1970","volume":"33","author":"F Fuchs","year":"2020","unstructured":"Fuchs F, Worrall D, Fischer V, Welling M (2020) Se (3)-transformers: 3d rototranslation equivariant attention networks. Adv Neural Inf Process Syst 33:1970\u20131981","journal-title":"Adv Neural Inf Process Syst"},{"key":"694_CR38","first-page":"1","volume":"32","author":"B Anderson","year":"2019","unstructured":"Anderson B, Hy TS, Kondor R (2019) Cormorant: covariant molecular neural networks. Adv Neural Inf Process Syst 32:1\u20131","journal-title":"Adv Neural Inf Process Syst"},{"key":"694_CR39","unstructured":"Weiler, M., Geiger, M., Welling, M., Boomsma, W., Cohen, T.S.: 3d steerable cnns: Learning rotationally equivariant features in volumetric data. Advances in Neural Information Processing Systems 31 (2018)"},{"key":"694_CR40","unstructured":"Lang, L., Weiler, M.: A wigner-eckart theorem for group equivariant convolution kernels. arXiv preprint arXiv:2010.10952 (2020)"},{"key":"694_CR41","doi-asserted-by":"crossref","unstructured":"Wang, P.-S., Liu, Y., Tong, X.: Deep octree-based cnns with output-guided skip connections for 3d shape and scene completion. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops, pp. 266\u2013267 (2020)","DOI":"10.1109\/CVPRW50498.2020.00141"},{"key":"694_CR42","unstructured":"Graham, B., Maaten, L.: Submanifold sparse convolutional networks. arXiv preprint arXiv:1706.01307 (2017)"},{"key":"694_CR43","doi-asserted-by":"crossref","unstructured":"Aoki, Y., Goforth, H., Srivatsan, R.A., Lucey, S.: Pointnetlk: Robust & efficient point cloud registration using pointnet. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 7163\u20137172 (2019)","DOI":"10.1109\/CVPR.2019.00733"},{"key":"694_CR44","doi-asserted-by":"crossref","unstructured":"Dai, A., Siddiqui, Y., Thies, J., Valentin, J., Nie\u00dfner, M.: Spsg: Self-supervised photometric scene generation from rgb-d scans. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 1747\u20131756 (2021)","DOI":"10.1109\/CVPR46437.2021.00179"},{"key":"694_CR45","doi-asserted-by":"crossref","unstructured":"Weder, S., Schonberger, J., Pollefeys, M., Oswald, M.R.: Routedfusion: Learning real-time depth map fusion. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 4887\u20134897 (2020)","DOI":"10.1109\/CVPR42600.2020.00494"},{"key":"694_CR46","doi-asserted-by":"crossref","unstructured":"Chen, H.-X., Huang, J., Mu, T.-J., Hu, S.-M.: Circle: Convolutional implicit reconstruction and completion for large-scale indoor scene. In: European Conference on Computer Vision, pp. 506\u2013522 (2022). Springer","DOI":"10.1007\/978-3-031-19824-3_30"},{"issue":"4\u20135","key":"694_CR47","doi-asserted-by":"publisher","first-page":"598","DOI":"10.1177\/0278364914551008","volume":"34","author":"T Whelan","year":"2015","unstructured":"Whelan T, Kaess M, Johannsson H, Fallon M, Leonard JJ, McDonald J (2015) Real-time large-scale dense rgb-d slam with volumetric fusion. Int J Rob Res 34(4\u20135):598\u2013626","journal-title":"Int J Rob Res"},{"key":"694_CR48","doi-asserted-by":"crossref","unstructured":"Kerl, C., Sturm, J., Cremers, D.: Dense visual slam for rgb-d cameras. In: 2013 IEEE\/RSJ International Conference on Intelligent Robots and Systems, pp. 2100\u20132106 (2013). IEEE","DOI":"10.1109\/IROS.2013.6696650"},{"key":"694_CR49","doi-asserted-by":"crossref","unstructured":"Endres, F., Hess, J., Engelhard, N., Sturm, J., Cremers, D., Burgard, W.: An evaluation of the rgb-d slam system. In: 2012 IEEE International Conference on Robotics and Automation, pp. 1691\u20131696 (2012). IEEE","DOI":"10.1109\/ICRA.2012.6225199"},{"issue":"1","key":"694_CR50","doi-asserted-by":"publisher","first-page":"137","DOI":"10.1016\/j.jvcir.2013.02.008","volume":"25","author":"J St\u00a8uckler","year":"2014","unstructured":"St\u00a8uckler J, Behnke S (2014) Multi-resolution surfel maps for efficient dense 3d modeling and tracking. J Vis Commun Image Represent 25(1):137\u2013147","journal-title":"J Vis Commun Image Represent"},{"key":"694_CR51","first-page":"16558","volume":"34","author":"Z Teed","year":"2021","unstructured":"Teed Z, Deng J (2021) Droid-slam: deep visual slam for monocular, stereo, and rgb-d cameras. Adv Neural Inf Process Syst 34:16558\u201316569","journal-title":"Adv Neural Inf Process Syst"},{"key":"694_CR52","doi-asserted-by":"crossref","unstructured":"Yang, X., Li, H., Zhai, H., Ming, Y., Liu, Y., Zhang, G.: Vox-fusion: Dense tracking and mapping with voxel-based neural implicit representation. In: 2022 IEEE International Symposium on Mixed and Augmented Reality (ISMAR), pp.499\u2013507 (2022). IEEE","DOI":"10.1109\/ISMAR55827.2022.00066"},{"key":"694_CR53","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Tosi, F., Mattoccia, S., Poggi, M.: Go-slam: Global optimization for consistent 3d instant reconstruction. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 3727\u20133737 (2023)","DOI":"10.1109\/ICCV51070.2023.00345"},{"key":"694_CR54","unstructured":"Hua, T., Bai, H., Cao, Z., Liu, M., Tao, D., Wang, L.: Hi-map: Hierarchical factorized radiance field for high-fidelity monocular dense mapping. arXiv preprint arXiv:2401.03203 (2024)"}],"container-title":["Intelligent Service Robotics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11370-026-00694-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11370-026-00694-6","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11370-026-00694-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,3]],"date-time":"2026-03-03T04:12:51Z","timestamp":1772511171000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11370-026-00694-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,3]]},"references-count":54,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2026,3]]}},"alternative-id":["694"],"URL":"https:\/\/doi.org\/10.1007\/s11370-026-00694-6","relation":{},"ISSN":["1861-2776","1861-2784"],"issn-type":[{"value":"1861-2776","type":"print"},{"value":"1861-2784","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,3]]},"assertion":[{"value":"23 July 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 January 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 March 2026","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 there are no conflicts of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflicts of interest"}}],"article-number":"42"}}