{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T03:14:26Z","timestamp":1767323666920,"version":"3.48.0"},"publisher-location":"Singapore","reference-count":35,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819557363","type":"print"},{"value":"9789819557370","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"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":[[2026]]},"DOI":"10.1007\/978-981-95-5737-0_32","type":"book-chapter","created":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T03:10:21Z","timestamp":1767323421000},"page":"453-467","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["DPGS-SLAM: Gaussian Splatting SLAM for\u00a0Dynamic Scenes with\u00a0Planar Constraints"],"prefix":"10.1007","author":[{"given":"Yuanze","family":"Gui","sequence":"first","affiliation":[]},{"given":"Xinggang","family":"Hu","sequence":"additional","affiliation":[]},{"given":"Xudong","family":"Liu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2026,1,2]]},"reference":[{"issue":"1","key":"32_CR1","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1145\/3503250","volume":"65","author":"B Mildenhall","year":"2021","unstructured":"Mildenhall, B., Srinivasan, P.P., Tancik, M., Barron, J.T., Ramamoorthi, R., Ng, R.: NeRF: representing scenes as neural radiance fields for view synthesis. Commun. ACM 65(1), 99\u2013106 (2021)","journal-title":"Commun. ACM"},{"key":"32_CR2","doi-asserted-by":"crossref","unstructured":"Kerbl, B., Kopanas, G., Leimk\u00fchler, T., Drettakis, G.: 3D Gaussian splatting for real-time radiance field rendering. ACM Trans. Graph. 42(4), 1\u201314 (2023). 139","DOI":"10.1145\/3592433"},{"key":"32_CR3","doi-asserted-by":"crossref","unstructured":"Zhu, Z., et al.: 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":"32_CR4","doi-asserted-by":"crossref","unstructured":"Wang, H., Wang, J., Agapito, L.: Co-SLAM: joint coordinate and sparse parametric encodings for neural real-time slam. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 13293\u201313302 (2023)","DOI":"10.1109\/CVPR52729.2023.01277"},{"key":"32_CR5","doi-asserted-by":"crossref","unstructured":"Huang, H., Li, L., Cheng, H., Yeung, S.-K.: Photo-SLAM: real-time simultaneous localization and photorealistic mapping for monocular stereo and RGB-D cameras. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 21584\u201321593 (2024)","DOI":"10.1109\/CVPR52733.2024.02039"},{"key":"32_CR6","doi-asserted-by":"crossref","unstructured":"Yan, C., et al.: GS-SLAM: dense visual slam with 3D Gaussian splatting. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 19595\u201319604 (2024)","DOI":"10.1109\/CVPR52733.2024.01853"},{"key":"32_CR7","doi-asserted-by":"crossref","unstructured":"Matsuki, H., Murai, R., Kelly, P.H.J., Davison, A.J.: Gaussian splatting SLAM. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 18039\u201318048 (2024)","DOI":"10.1109\/CVPR52733.2024.01708"},{"key":"32_CR8","doi-asserted-by":"crossref","unstructured":"Ruan, C., Zang, Q., Zhang, K., Huang, K.: DN-SLAM: a visual SLAM with ORB features and nerf mapping in dynamic environments. IEEE Sens. J. (2023)","DOI":"10.1109\/JSEN.2023.3345877"},{"key":"32_CR9","doi-asserted-by":"crossref","unstructured":"Xu, Z., Niu, J., Li, Q., Ren, T., Chen, C.: NID-SLAM: neural implicit representation-based RGB-D SLAM in dynamic environments. arXiv preprint arXiv:2401.01189 (2024)","DOI":"10.1109\/ICME57554.2024.10687512"},{"key":"32_CR10","doi-asserted-by":"crossref","unstructured":"Jiang, H., Xu, Y., Li, K., Feng, J.,\u00a0Zhang, L.: RoDyn-SLAM: robust dynamic dense RGB-D SLAM with neural radiance fields. IEEE Robot. Autom. Lett. (2024)","DOI":"10.1109\/LRA.2024.3427554"},{"key":"32_CR11","doi-asserted-by":"crossref","unstructured":"Li, M., Chen, W.,\u00a0Cheng, N., Xu, J., Li, D., Wang, H.: GARAD-SLAM: 3D Gaussian splatting for real-time anti dynamic SLAM. arXiv preprint arXiv:2502.03228 (2025)","DOI":"10.1109\/ICRA55743.2025.11128757"},{"key":"32_CR12","unstructured":"Xu, Y., Jiang, H., Xiao, Z., Feng, J.,\u00a0Zhang, L.: DG-SLAM: robust dynamic gaussian splatting slam with hybrid pose optimization. In: The Thirty-eighth Annual Conference on Neural Information Processing Systems (2024)"},{"key":"32_CR13","doi-asserted-by":"crossref","unstructured":"Peng, Z., et al.: RTG-SLAM: real-time 3D reconstruction at scale using gaussian splatting. In: ACM SIGGRAPH 2024 Conference Papers, pp. 1\u201311 (2024)","DOI":"10.1145\/3641519.3657455"},{"key":"32_CR14","doi-asserted-by":"crossref","unstructured":"Sun, S., Mielle, M., Lilienthal, A.J., Magnusson, M.: High-fidelity SLAM using gaussian splatting with rendering-guided densification and regularized optimization. arXiv preprint arXiv:2403.12535 (2024)","DOI":"10.1109\/IROS58592.2024.10802373"},{"key":"32_CR15","doi-asserted-by":"crossref","unstructured":"Chen, D., et al.: VIP-SLAM: an efficient tightly-coupled RGB-D visual inertial planar SLAM. In: 2022 International Conference on Robotics and Automation (ICRA), pp. 5615\u20135621. IEEE (2022)","DOI":"10.1109\/ICRA46639.2022.9812354"},{"key":"32_CR16","doi-asserted-by":"crossref","unstructured":"Hu, X., Wu, Y., Zhao, M., Yang, L., Zhang, X., Ji, X.: PAS-SLAM: a visual slam system for planar-ambiguous scenes. IEEE Trans. Circ. Syst. Video Technol. (2024)","DOI":"10.1109\/TCSVT.2024.3491506"},{"key":"32_CR17","series-title":"LNCS","doi-asserted-by":"publisher","first-page":"441","DOI":"10.1007\/978-3-031-72761-0_25","volume-title":"ECCV 2024","author":"Y Li","year":"2024","unstructured":"Li, Y., Lyu, C., Di, Y., Zhai, G., Lee, G.H., Tombari, F.: GeoGaussian: geometry-aware Gaussian splatting for scene rendering. In: Leonardis, A., Ricci, E., Roth, S., Russakovsky, O., Sattler, T., Varol, G. (eds.) ECCV 2024. LNCS, vol. 15093, pp. 441\u2013457. Springer, Cham (2024). https:\/\/doi.org\/10.1007\/978-3-031-72761-0_25"},{"key":"32_CR18","unstructured":"Jocher, G., Chaurasia, A., Qiu, J.: Ultralytics YOLOv8 (2023)"},{"key":"32_CR19","unstructured":"Zhao, X., et al.: Fast segment anything. arXiv preprint arXiv:2306.12156 (2023)"},{"key":"32_CR20","doi-asserted-by":"crossref","unstructured":"Yu, C., et al.: DS-SLAM: a semantic visual slam towards dynamic environments. In: 2018 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 1168\u20131174. IEEE (2018)","DOI":"10.1109\/IROS.2018.8593691"},{"issue":"4","key":"32_CR21","doi-asserted-by":"publisher","first-page":"4076","DOI":"10.1109\/LRA.2018.2860039","volume":"3","author":"B Bescos","year":"2018","unstructured":"Bescos, B., F\u00e1cil, J.M., Civera, J., Neira, J.: DynaSLAM: tracking, mapping, and inpainting in dynamic scenes. IEEE Robot. Autom. Lett. 3(4), 4076\u20134083 (2018)","journal-title":"IEEE Robot. Autom. Lett."},{"key":"32_CR22","doi-asserted-by":"crossref","unstructured":"Hu, X., et al.: CFP-SLAM: a real-time visual SLAM based on coarse-to-fine probability in dynamic environments. In: 2022 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 4399\u20134406. IEEE (2022)","DOI":"10.1109\/IROS47612.2022.9981826"},{"key":"32_CR23","doi-asserted-by":"publisher","unstructured":"Klappstein, J., Vaudrey, T., Rabe, C., Wedel, A., Klette, R.: Moving object segmentation using optical flow and depth information. In: Wada, T., Huang, F., Lin, S. (eds.) PSIVT 2009. LNCS, vol. 5414, pp. 611\u2013623. Springer, Heidelberg (2009). https:\/\/doi.org\/10.1007\/978-3-540-92957-4_53","DOI":"10.1007\/978-3-540-92957-4_53"},{"issue":"12","key":"32_CR24","doi-asserted-by":"publisher","first-page":"576","DOI":"10.1080\/01691864.2019.1610060","volume":"33","author":"J Cheng","year":"2019","unstructured":"Cheng, J., Sun, Y., Meng, M.Q.-H.: Improving monocular visual SLAM in dynamic environments: an optical-flow-based approach. Adv. Robot. 33(12), 576\u2013589 (2019)","journal-title":"Adv. Robot."},{"key":"32_CR25","doi-asserted-by":"crossref","unstructured":"Shen, S., Cai, Y., Wang, W., Scherer, S.: DytanVO: joint refinement of visual odometry and motion segmentation in dynamic environments. In: 2023 IEEE International Conference on Robotics and Automation (ICRA), pp. 4048\u20134055. IEEE (2023)","DOI":"10.1109\/ICRA48891.2023.10161306"},{"key":"32_CR26","doi-asserted-by":"crossref","unstructured":"Hu, J., et al.: CG-SLAM: efficient dense RGB-D SLAM in a consistent uncertainty-aware 3D Gaussian field. In: European Conference on Computer Vision, pp. 93\u2013112. Springer (2025)","DOI":"10.1007\/978-3-031-72698-9_6"},{"key":"32_CR27","doi-asserted-by":"crossref","unstructured":"Keetha, N., et al.: SplaTAM: splat track & map 3D Gaussians for dense RGB-D SLAM. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 21357\u201321366 (2024)","DOI":"10.1109\/CVPR52733.2024.02018"},{"key":"32_CR28","doi-asserted-by":"crossref","unstructured":"Zheng, J., Zhu, Z., Bieri, V., Pollefeys, M., Peng, S., Armeni, I.: WILDGS-SLAM: monocular Gaussian splatting SLAM in dynamic environments. In: Proceedings of the Computer Vision and Pattern Recognition Conference, pp. 11461\u201311471 (2025)","DOI":"10.1109\/CVPR52734.2025.01070"},{"issue":"4","key":"32_CR29","doi-asserted-by":"publisher","first-page":"625","DOI":"10.3390\/rs17040625","volume":"17","author":"F Zhu","year":"2025","unstructured":"Zhu, F., Zhao, Y., Chen, Z., Jiang, C., Zhu, H., Xiaoxi, H.: DYGS-SLAM: realistic map reconstruction in dynamic scenes based on double-constrained visual SLAM. Remote Sens. 17(4), 625 (2025)","journal-title":"Remote Sens."},{"key":"32_CR30","doi-asserted-by":"crossref","unstructured":"Liu, H., et al.: SDD-SLAM: semantic-driven dynamic SLAM with Gaussian splatting. IEEE Robot. Autom. Lett. (2025)","DOI":"10.1109\/LRA.2025.3561565"},{"key":"32_CR31","doi-asserted-by":"crossref","unstructured":"Feng, C., Taguchi, Y., Kamat, V.R.: Fast plane extraction in organized point clouds using agglomerative hierarchical clustering. In: 2014 IEEE International Conference on Robotics and Automation (ICRA), pp. 6218\u20136225. IEEE (2014)","DOI":"10.1109\/ICRA.2014.6907776"},{"issue":"6","key":"32_CR32","doi-asserted-by":"publisher","first-page":"1874","DOI":"10.1109\/TRO.2021.3075644","volume":"37","author":"C Campos","year":"2021","unstructured":"Campos, C., Elvira, R., Rodr\u00edguez, J.J.G., Montiel, J.M.M., Tard\u00f3s, J.D.: ORB-SLAM3: an accurate open-source library for visual, visual-inertial, and multimap SLAM. IEEE Trans. Rob. 37(6), 1874\u20131890 (2021)","journal-title":"IEEE Trans. Rob."},{"key":"32_CR33","doi-asserted-by":"crossref","unstructured":"Sturm, J., Engelhard, N., Endres, F., Burgard, W., Cremers, D.: A benchmark for the evaluation of RGB-D SLAM systems. In: 2012 IEEE\/RSJ International Conference on Intelligent Robots and Systems, pp. 573\u2013580. IEEE (2012)","DOI":"10.1109\/IROS.2012.6385773"},{"key":"32_CR34","doi-asserted-by":"crossref","unstructured":"Palazzolo, E., Behley, J., Lottes, P., Giguere, P., Stachniss, C.: Refusion: 3D reconstruction in dynamic environments for RGB-D cameras exploiting residuals. In: 2019 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 7855\u20137862. IEEE (2019)","DOI":"10.1109\/IROS40897.2019.8967590"},{"key":"32_CR35","doi-asserted-by":"crossref","unstructured":"Johari, M.M., Carta, C., Fleuret, F.: ESLAM: efficient dense SLAM system based on hybrid representation of signed distance fields. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 17408\u201317419 (2023)","DOI":"10.1109\/CVPR52729.2023.01670"}],"container-title":["Lecture Notes in Computer Science","Pattern Recognition and Computer Vision"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-95-5737-0_32","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T03:10:23Z","timestamp":1767323423000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-95-5737-0_32"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"ISBN":["9789819557363","9789819557370"],"references-count":35,"URL":"https:\/\/doi.org\/10.1007\/978-981-95-5737-0_32","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]},"assertion":[{"value":"2 January 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PRCV","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Chinese Conference on Pattern Recognition and Computer Vision  (PRCV)","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Shanghai","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":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 October 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18 October 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ccprcv2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/2025.prcv.cn\/index.asp","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}