{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T16:07:03Z","timestamp":1775837223650,"version":"3.50.1"},"publisher-location":"Cham","reference-count":44,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031726422","type":"print"},{"value":"9783031726439","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,11,22]],"date-time":"2024-11-22T00:00:00Z","timestamp":1732233600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,11,22]],"date-time":"2024-11-22T00:00:00Z","timestamp":1732233600000},"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\/978-3-031-72643-9_17","type":"book-chapter","created":{"date-parts":[[2024,11,21]],"date-time":"2024-11-21T20:47:35Z","timestamp":1732222055000},"page":"281-297","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":32,"title":["Analytic-Splatting: Anti-Aliased 3D Gaussian Splatting via\u00a0Analytic Integration"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-2195-7918","authenticated-orcid":false,"given":"Zhihao","family":"Liang","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9611-6697","authenticated-orcid":false,"given":"Qi","family":"Zhang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6082-4966","authenticated-orcid":false,"given":"Wenbo","family":"Hu","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0191-7086","authenticated-orcid":false,"given":"Lei","family":"Zhu","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0006-7838-3103","authenticated-orcid":false,"given":"Ying","family":"Feng","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2661-5700","authenticated-orcid":false,"given":"Kui","family":"Jia","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,11,22]]},"reference":[{"key":"17_CR1","doi-asserted-by":"crossref","unstructured":"Akeley, K.: Reality engine graphics. In: Conference on Computer Graphics and Interactive Techniques, pp. 109\u2013116 (1993)","DOI":"10.1145\/166117.166131"},{"key":"17_CR2","doi-asserted-by":"crossref","unstructured":"Barron, J.T., Mildenhall, B., Tancik, M., Hedman, P., Martin-Brualla, R., Srinivasan, P.P.: Mip-nerf: a multiscale representation for anti-aliasing neural radiance fields. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 5855\u20135864 (2021)","DOI":"10.1109\/ICCV48922.2021.00580"},{"key":"17_CR3","doi-asserted-by":"crossref","unstructured":"Barron, J.T., Mildenhall, B., Verbin, D., Srinivasan, P.P., Hedman, P.: Mip-nerf 360: unbounded anti-aliased neural radiance fields. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 5470\u20135479 (2022)","DOI":"10.1109\/CVPR52688.2022.00539"},{"key":"17_CR4","doi-asserted-by":"crossref","unstructured":"Barron, J.T., Mildenhall, B., Verbin, D., Srinivasan, P.P., Hedman, P.: Zip-nerf: anti-aliased grid-based neural radiance fields. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision (2023)","DOI":"10.1109\/ICCV51070.2023.01804"},{"issue":"1","key":"17_CR5","first-page":"114","volume":"2","author":"SR Bowling","year":"2009","unstructured":"Bowling, S.R., Khasawneh, M.T., Kaewkuekool, S., Cho, B.R.: A logistic approximation to the cumulative normal distribution. J. Ind. Eng. Manage. 2(1), 114\u2013127 (2009)","journal-title":"J. Ind. Eng. Manage."},{"key":"17_CR6","doi-asserted-by":"publisher","unstructured":"Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: Tensorf: tensorial radiance fields. In: European Conference on Computer Vision, pp. 333\u2013350. Springer (2022). https:\/\/doi.org\/10.1007\/978-3-031-19824-3_20","DOI":"10.1007\/978-3-031-19824-3_20"},{"key":"17_CR7","unstructured":"Chen, H., Li, C., Lee, G.H.: Neusg: Neural implicit surface reconstruction with 3d gaussian splatting guidance. arXiv preprint arXiv:2312.00846 (2023)"},{"key":"17_CR8","unstructured":"Feng, Y., et\u00a0al.: Gaussian splashing: Dynamic fluid synthesis with gaussian splatting. arXiv preprint arXiv:2401.15318 (2024)"},{"key":"17_CR9","doi-asserted-by":"crossref","unstructured":"Fridovich-Keil, S., Yu, A., Tancik, M., Chen, Q., Recht, B., Kanazawa, A.: Plenoxels: Radiance fields without neural networks. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 5501\u20135510 (2022)","DOI":"10.1109\/CVPR52688.2022.00542"},{"key":"17_CR10","doi-asserted-by":"crossref","unstructured":"Gao, Q., Xu, Q., Su, H., Neumann, U., Xu, Z.: Strivec: sparse tri-vector radiance fields. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 17569\u201317579 (2023)","DOI":"10.1109\/ICCV51070.2023.01611"},{"key":"17_CR11","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"},{"issue":"6","key":"17_CR12","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3272127.3275084","volume":"37","author":"P Hedman","year":"2018","unstructured":"Hedman, P., Philip, J., Price, T., Frahm, J.M., Drettakis, G., Brostow, G.: Deep blending for free-viewpoint image-based rendering. ACM Trans. Graph. (ToG) 37(6), 1\u201315 (2018)","journal-title":"ACM Trans. Graph. (ToG)"},{"key":"17_CR13","doi-asserted-by":"crossref","unstructured":"Hu, L., Zhang, H., Zhang, Y., Zhou, B., Liu, B., Zhang, S., Nie, L.: Gaussianavatar: Towards realistic human avatar modeling from a single video via animatable 3d gaussians. arXiv preprint arXiv:2312.02134 (2023)","DOI":"10.1109\/CVPR52733.2024.00067"},{"key":"17_CR14","doi-asserted-by":"crossref","unstructured":"Hu, W., et al.: Tri-miprf: tri-mip representation for efficient anti-aliasing neural radiance fields. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 19774\u201319783 (2023)","DOI":"10.1109\/ICCV51070.2023.01811"},{"key":"17_CR15","doi-asserted-by":"crossref","unstructured":"Huang, X., Zhang, Q., Feng, Y., Li, H., Wang, X., Wang, Q.: Hdr-nerf: high dynamic range neural radiance fields. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 18398\u201318408 (2022)","DOI":"10.1109\/CVPR52688.2022.01785"},{"key":"17_CR16","doi-asserted-by":"crossref","unstructured":"Huang, Z., Liang, Z., Zhang, H., Lin, Y., Jia, K.: Sur2f: A hybrid representation for high-quality and efficient surface reconstruction from multi-view images. arXiv preprint arXiv:2401.03704 (2024)","DOI":"10.1007\/978-3-031-73027-6_1"},{"key":"17_CR17","doi-asserted-by":"crossref","unstructured":"Jiang, Y., et al.: Gaussianshader: 3d gaussian splatting with shading functions for reflective surfaces. arXiv preprint arXiv:2311.17977 (2023)","DOI":"10.1109\/CVPR52733.2024.00509"},{"key":"17_CR18","doi-asserted-by":"crossref","unstructured":"Kerbl, B., Kopanas, G., Leimk\u00fchler, T., Drettakis, G.: 3d gaussian splatting for real-time radiance field rendering. ACM Transactions on Graphics 42(4) (2023)","DOI":"10.1145\/3592433"},{"issue":"4","key":"17_CR19","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3072959.3073599","volume":"36","author":"A Knapitsch","year":"2017","unstructured":"Knapitsch, A., Park, J., Zhou, Q.Y., Koltun, V.: Tanks and temples: benchmarking large-scale scene reconstruction. ACM Trans. Graph. (ToG) 36(4), 1\u201313 (2017)","journal-title":"ACM Trans. Graph. (ToG)"},{"key":"17_CR20","doi-asserted-by":"crossref","unstructured":"Kuznetsov, A.: Neumip: multi-resolution neural materials. ACM Trans. Graph.(ToG) 40(4) (2021)","DOI":"10.1145\/3476576.3476763"},{"key":"17_CR21","unstructured":"Li, R., Tancik, M., Kanazawa, A.: Nerfacc: A general nerf acceleration toolbox. arXiv preprint arXiv:2210.04847 (2022)"},{"key":"17_CR22","doi-asserted-by":"crossref","unstructured":"Liang, Z., Zhang, Q., Feng, Y., Shan, Y., Jia, K.: Gs-ir: 3d gaussian splatting for inverse rendering. arXiv preprint arXiv:2311.16473 (2023)","DOI":"10.1109\/CVPR52733.2024.02045"},{"key":"17_CR23","doi-asserted-by":"crossref","unstructured":"Lin, C.H., Ma, W.C., Torralba, A., Lucey, S.: Barf: bundle-adjusting neural radiance fields. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 5741\u20135751 (2021)","DOI":"10.1109\/ICCV48922.2021.00569"},{"key":"17_CR24","doi-asserted-by":"crossref","unstructured":"Ma, L., et al.: Deblur-nerf: Neural radiance fields from blurry images. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 12861\u201312870 (2022)","DOI":"10.1109\/CVPR52688.2022.01252"},{"key":"17_CR25","doi-asserted-by":"crossref","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. In: European Conference on Computer Vision, pp. 405\u2013421 (2020)","DOI":"10.1007\/978-3-030-58452-8_24"},{"issue":"4","key":"17_CR26","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3528223.3530127","volume":"41","author":"T M\u00fcller","year":"2022","unstructured":"M\u00fcller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Trans. Graph. (ToG) 41(4), 1\u201315 (2022)","journal-title":"ACM Trans. Graph. (ToG)"},{"key":"17_CR27","doi-asserted-by":"crossref","unstructured":"Park, K., et al.: Nerfies: deformable neural radiance fields. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 5865\u20135874 (2021)","DOI":"10.1109\/ICCV48922.2021.00581"},{"key":"17_CR28","doi-asserted-by":"crossref","unstructured":"Saito, S., Schwartz, G., Simon, T., Li, J., Nam, G.: Relightable gaussian codec avatars. arXiv preprint arXiv:2312.03704 (2023)","DOI":"10.1109\/CVPR52733.2024.00021"},{"key":"17_CR29","unstructured":"Shi, Y., et\u00a0al.: Gir: 3d gaussian inverse rendering for relightable scene factorization. arXiv preprint arXiv:2312.05133 (2023)"},{"key":"17_CR30","doi-asserted-by":"crossref","unstructured":"Sun, C., Sun, M., Chen, H.T.: Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 5459\u20135469 (2022)","DOI":"10.1109\/CVPR52688.2022.00538"},{"key":"17_CR31","unstructured":"Wang, P., Liu, L., Liu, Y., Theobalt, C., Komura, T., Wang, W.: Neus: Learning neural implicit surfaces by volume rendering for multi-view reconstruction. arXiv preprint arXiv:2106.10689 (2021)"},{"issue":"4","key":"17_CR32","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3306346.3322936","volume":"38","author":"L Wu","year":"2019","unstructured":"Wu, L., Zhao, S., Yan, L.Q., Ramamoorthi, R.: Accurate appearance preserving prefiltering for rendering displacement-mapped surfaces. ACM Trans. Graph. (ToG) 38(4), 1\u201314 (2019)","journal-title":"ACM Trans. Graph. (ToG)"},{"key":"17_CR33","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":"17_CR34","doi-asserted-by":"crossref","unstructured":"Xu, Q., et al.: Point-nerf: point-based neural radiance fields. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 5438\u20135448 (2022)","DOI":"10.1109\/CVPR52688.2022.00536"},{"key":"17_CR35","first-page":"4805","volume":"34","author":"L Yariv","year":"2021","unstructured":"Yariv, L., Gu, J., Kasten, Y., Lipman, Y.: Volume rendering of neural implicit surfaces. Adv. Neural. Inf. Process. Syst. 34, 4805\u20134815 (2021)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"17_CR36","doi-asserted-by":"crossref","unstructured":"Yu, A., Li, R., Tancik, M., Li, H., Ng, R., Kanazawa, A.: Plenoctrees for real-time rendering of neural radiance fields. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 5752\u20135761 (2021)","DOI":"10.1109\/ICCV48922.2021.00570"},{"key":"17_CR37","doi-asserted-by":"crossref","unstructured":"Yu, Z., Chen, A., Huang, B., Sattler, T., Geiger, A.: Mip-splatting: Alias-free 3d gaussian splatting. arXiv preprint arXiv:2311.16493 (2023)","DOI":"10.1109\/CVPR52733.2024.01839"},{"key":"17_CR38","doi-asserted-by":"crossref","unstructured":"Zhang, R., Isola, P., Efros, A.A., Shechtman, E., Wang, O.: The unreasonable effectiveness of deep features as a perceptual metric. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 586\u2013595 (2018)","DOI":"10.1109\/CVPR.2018.00068"},{"key":"17_CR39","doi-asserted-by":"crossref","unstructured":"Zheng, S., et al.: Gps-gaussian: Generalizable pixel-wise 3d gaussian splatting for real-time human novel view synthesis. arXiv preprint arXiv:2312.02155 (2023)","DOI":"10.1109\/CVPR52733.2024.01861"},{"key":"17_CR40","doi-asserted-by":"crossref","unstructured":"Zhuang, Y., et al.: Anti-aliased neural implicit surfaces with encoding level of detail. In: SIGGRAPH Asia 2023 Conference Papers, pp. 1\u201310 (2023)","DOI":"10.1145\/3610548.3618197"},{"key":"17_CR41","unstructured":"Zielonka, W., Bagautdinov, T., Saito, S., Zollh\u00f6fer, M., Thies, J., Romero, J.: Drivable 3d gaussian avatars. arXiv preprint arXiv:2311.08581 (2023)"},{"key":"17_CR42","doi-asserted-by":"crossref","unstructured":"Zwicker, M., Pfister, H., Van\u00a0Baar, J., Gross, M.: Ewa volume splatting. In: Proceedings Visualization, 2001. VIS\u201901, pp. 29\u2013538. IEEE (2001)","DOI":"10.1145\/383259.383300"},{"key":"17_CR43","doi-asserted-by":"crossref","unstructured":"Zwicker, M., Pfister, H., Van\u00a0Baar, J., Gross, M.: Surface splatting. In: Proceedings of the 28th annual conference on Computer graphics and interactive techniques, pp. 371\u2013378 (2001)","DOI":"10.1145\/383259.383300"},{"issue":"3","key":"17_CR44","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. Visual Comput. Graphics 8(3), 223\u2013238 (2002)","journal-title":"IEEE Trans. Visual Comput. Graphics"}],"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\/978-3-031-72643-9_17","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,1]],"date-time":"2024-12-01T20:03:13Z","timestamp":1733083393000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-72643-9_17"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,22]]},"ISBN":["9783031726422","9783031726439"],"references-count":44,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-72643-9_17","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,11,22]]},"assertion":[{"value":"22 November 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"}}]}}