{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T15:22:13Z","timestamp":1782314533160,"version":"3.54.5"},"publisher-location":"Cham","reference-count":32,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031726972","type":"print"},{"value":"9783031726989","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,10,26]],"date-time":"2024-10-26T00:00:00Z","timestamp":1729900800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,10,26]],"date-time":"2024-10-26T00:00:00Z","timestamp":1729900800000},"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\/978-3-031-72698-9_3","type":"book-chapter","created":{"date-parts":[[2024,10,25]],"date-time":"2024-10-25T04:45:57Z","timestamp":1729831557000},"page":"37-53","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["Texture-GS: Disentangling the\u00a0Geometry and\u00a0Texture for\u00a03D Gaussian Splatting Editing"],"prefix":"10.1007","author":[{"given":"Tian-Xing","family":"Xu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenbo","family":"Hu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yu-Kun","family":"Lai","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ying","family":"Shan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Song-Hai","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,10,26]]},"reference":[{"key":"3_CR1","doi-asserted-by":"publisher","first-page":"153","DOI":"10.1007\/s11263-016-0902-9","volume":"120","author":"H Aan\u00e6s","year":"2016","unstructured":"Aan\u00e6s, H., Jensen, R.R., Vogiatzis, G., Tola, E., Dahl, A.B.: Large-scale data for multiple-view stereopsis. Int. J. Comput. Vis. 120, 153\u2013168 (2016)","journal-title":"Int. J. Comput. Vis."},{"key":"3_CR2","doi-asserted-by":"crossref","unstructured":"Chen, Y., et al.: GaussianEditor: swift and controllable 3D editing with gaussian splatting. arXiv preprint arXiv:2311.14521 (2023)","DOI":"10.1109\/CVPR52733.2024.02029"},{"key":"3_CR3","doi-asserted-by":"crossref","unstructured":"Chen, Y., et al.: UV volumes for real-time rendering of editable free-view human performance. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 16621\u201316631 (2023)","DOI":"10.1109\/CVPR52729.2023.01595"},{"key":"3_CR4","doi-asserted-by":"crossref","unstructured":"Chen, Z., Yin, K., Fidler, S.: AUV-Net: learning aligned UV maps for texture transfer and synthesis. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 1465\u20131474 (2022)","DOI":"10.1109\/CVPR52688.2022.00152"},{"key":"3_CR5","doi-asserted-by":"publisher","first-page":"580","DOI":"10.1007\/978-3-031-19836-6_33","volume-title":"Computer Vision \u2013 ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23\u201327, 2022, Proceedings, Part XXXVII","author":"S Das","year":"2022","unstructured":"Das, S., Ma, K., Shu, Z., Samaras, D.: Learning an\u00a0isometric surface parameterization for\u00a0texture unwrapping. In: Avidan, S., Brostow, G., Ciss\u00e9, M., Farinella, G.M., Hassner, T. (eds.) Computer Vision \u2013 ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23\u201327, 2022, Proceedings, Part XXXVII, pp. 580\u2013597. Springer Nature Switzerland, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-19836-6_33"},{"key":"3_CR6","doi-asserted-by":"crossref","unstructured":"Deitke, M., et al.: Objaverse: a universe of annotated 3D objects. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 13142\u201313153 (2023)","DOI":"10.1109\/CVPR52729.2023.01263"},{"key":"3_CR7","doi-asserted-by":"crossref","unstructured":"Downs, L., et al.: Google scanned objects: a high-quality dataset of 3D scanned household items. In: 2022 International Conference on Robotics and Automation (ICRA), pp. 2553\u20132560. IEEE (2022)","DOI":"10.1109\/ICRA46639.2022.9811809"},{"key":"3_CR8","doi-asserted-by":"crossref","unstructured":"Fang, J., Wang, J., Zhang, X., Xie, L., Tian, Q.: GaussianEditor: editing 3D gaussians delicately with text instructions. arXiv preprint arXiv:2311.16037 (2023)","DOI":"10.1109\/CVPR52733.2024.01975"},{"key":"3_CR9","doi-asserted-by":"crossref","unstructured":"Gu\u00e9don, A., Lepetit, V.: Sugar: surface-aligned gaussian splatting for efficient 3D mesh reconstruction and high-quality mesh rendering. arXiv preprint arXiv:2311.12775 (2023)","DOI":"10.1109\/CVPR52733.2024.00512"},{"key":"3_CR10","unstructured":"Hu, X., et al.: Semantic anything in 3D gaussians. arXiv preprint arXiv:2401.17857 (2024)"},{"key":"3_CR11","doi-asserted-by":"crossref","unstructured":"Huang, J., Yu, H.: Point\u2019n move: interactive scene object manipulation on gaussian splatting radiance fields. arXiv preprint arXiv:2311.16737 (2023)","DOI":"10.1049\/ipr2.13190"},{"key":"3_CR12","doi-asserted-by":"crossref","unstructured":"Huang, Y.H., Sun, Y.T., Yang, Z., Lyu, X., Cao, Y.P., Qi, X.: SC-GS: sparse-controlled gaussian splatting for editable dynamic scenes. arXiv preprint arXiv:2312.14937 (2023)","DOI":"10.1109\/CVPR52733.2024.00404"},{"key":"3_CR13","doi-asserted-by":"crossref","unstructured":"Jiang, Y., Tu, J., Liu, Y., Gao, X., Long, X., Wang, W., Ma, Y.: Gaussianshader: 3D gaussian splatting with shading functions for reflective surfaces. arXiv preprint arXiv:2311.17977 (2023)","DOI":"10.1109\/CVPR52733.2024.00509"},{"key":"3_CR14","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) (2023)","DOI":"10.1145\/3592433"},{"key":"3_CR15","unstructured":"Kirillov, A., et\u00a0al.: Segment anything. arXiv preprint arXiv:2304.02643 (2023)"},{"issue":"6","key":"3_CR16","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3550454.3555494","volume":"41","author":"L Ma","year":"2022","unstructured":"Ma, L., et al.: Neural parameterization for dynamic human head editing. ACM Trans. Graph. (TOG) 41(6), 1\u201315 (2022)","journal-title":"ACM Trans. Graph. (TOG)"},{"issue":"1","key":"3_CR17","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":"3_CR18","doi-asserted-by":"crossref","unstructured":"Moriyasu, K.: An elementary primer for gauge theory. World Scientific (1983)","DOI":"10.1142\/0049"},{"key":"3_CR19","doi-asserted-by":"crossref","unstructured":"Rombach, R., Blattmann, A., Lorenz, D., Esser, P., Ommer, B.: High-resolution image synthesis with latent diffusion models. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 10684\u201310695 (2022)","DOI":"10.1109\/CVPR52688.2022.01042"},{"key":"3_CR20","doi-asserted-by":"crossref","unstructured":"Sch\u00f6nberger, J.L., Frahm, J.M.: Structure-from-motion revisited. In: Conference on Computer Vision and Pattern Recognition (CVPR) (2016)","DOI":"10.1109\/CVPR.2016.445"},{"key":"3_CR21","doi-asserted-by":"crossref","unstructured":"Srinivasan, P.P., Garbin, S.J., Verbin, D., Barron, J.T., Mildenhall, B.: Nuvo: neural UV mapping for unruly 3D representations. arXiv preprint arXiv:2312.05283 (2023)","DOI":"10.1007\/978-3-031-72933-1_2"},{"key":"3_CR22","doi-asserted-by":"crossref","unstructured":"Wang, X., et al.: Seal-3D: interactive pixel-level editing for neural radiance fields. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 17683\u201317693 (2023)","DOI":"10.1109\/ICCV51070.2023.01621"},{"key":"3_CR23","doi-asserted-by":"crossref","unstructured":"Xiang, F., Xu, Z., Hasan, M., Hold-Geoffroy, Y., Sunkavalli, K., Su, H.: NeuTex: neural texture mapping for volumetric neural rendering. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 7119\u20137128 (2021)","DOI":"10.1109\/CVPR46437.2021.00704"},{"key":"3_CR24","doi-asserted-by":"crossref","unstructured":"Xie, T., et al.: PhysGaussian: physics-integrated 3D gaussians for generative dynamics. arXiv preprint arXiv:2311.12198 (2023)","DOI":"10.1109\/CVPR52733.2024.00420"},{"key":"3_CR25","unstructured":"Xu, B., Hu, J., Hou, F., Lin, K.Y., Wu, W., Qian, C., He, Y.: Bi-directional deformation for parameterization of neural implicit surfaces. arXiv preprint arXiv:2310.05524 (2023)"},{"key":"3_CR26","doi-asserted-by":"publisher","first-page":"597","DOI":"10.1007\/978-3-031-19787-1_34","volume-title":"Computer Vision \u2013 ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23\u201327, 2022, Proceedings, Part XVI","author":"B Yang","year":"2022","unstructured":"Yang, B., et al.: NeuMesh: learning disentangled neural mesh-based implicit field for\u00a0geometry and\u00a0texture editing. In: Avidan, S., Brostow, G., Ciss\u00e9, M., Farinella, G.M., Hassner, T. (eds.) Computer Vision \u2013 ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23\u201327, 2022, Proceedings, Part XVI, pp. 597\u2013614. Springer Nature Switzerland, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-19787-1_34"},{"key":"3_CR27","unstructured":"Yariv, L., et al.: Multiview neural surface reconstruction by disentangling geometry and appearance. In: Advances in Neural Information Processing Systems, vol. 33 (2020)"},{"key":"3_CR28","doi-asserted-by":"crossref","unstructured":"Ye, M., Danelljan, M., Yu, F., Ke, L.: Gaussian grouping: segment and edit anything in 3D scenes. arXiv preprint arXiv:2312.00732 (2023)","DOI":"10.1007\/978-3-031-73397-0_10"},{"key":"3_CR29","doi-asserted-by":"crossref","unstructured":"Yu, H., Julin, J., Milacski, Z.\u00c1., Niinuma, K., Jeni, L.A.: CoGS: controllable Gaussian splatting. arXiv preprint arXiv:2312.05664 (2023)","DOI":"10.1109\/CVPR52733.2024.02043"},{"key":"3_CR30","unstructured":"Zhan, F., Liu, L., Kortylewski, A., Theobalt, C.: General neural gauge fields. In: The Eleventh International Conference on Learning Representations, ICLR 2023, Kigali, Rwanda, May 1-5, 2023. OpenReview.net (2023). https:\/\/openreview.net\/pdf?id=XWkWK2UagFR"},{"key":"3_CR31","doi-asserted-by":"crossref","unstructured":"Zhou, S., et al.: Feature 3DGS: supercharging 3D gaussian splatting to enable distilled feature fields. arXiv preprint arXiv:2312.03203 (2023)","DOI":"10.1109\/CVPR52733.2024.02048"},{"issue":"3","key":"3_CR32","doi-asserted-by":"publisher","first-page":"223","DOI":"10.1109\/TVCG.2002.1021576","volume":"8","author":"M Zwicker","year":"2002","unstructured":"Zwicker, M., Pfister, H., Van Baar, J., Gross, M.: EWA splatting. IEEE Trans. Vis. Comput. Graph. 8(3), 223\u2013238 (2002)","journal-title":"IEEE Trans. Vis. Comput. Graph."}],"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\/978-3-031-72698-9_3","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,30]],"date-time":"2024-11-30T07:20:00Z","timestamp":1732951200000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-72698-9_3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,10,26]]},"ISBN":["9783031726972","9783031726989"],"references-count":32,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-72698-9_3","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,10,26]]},"assertion":[{"value":"26 October 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"}}]}}