{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,16]],"date-time":"2026-02-16T12:29:48Z","timestamp":1771244988152,"version":"3.50.1"},"publisher-location":"Singapore","reference-count":32,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819569496","type":"print"},{"value":"9789819569502","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\/978-981-95-6950-2_16","type":"book-chapter","created":{"date-parts":[[2026,2,16]],"date-time":"2026-02-16T11:59:39Z","timestamp":1771243179000},"page":"219-232","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Stereo3D-NeRF: Generating 3D Visualizations with Paired Stereoscopic Views"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-3245-1455","authenticated-orcid":false,"given":"Yongxiang","family":"Wang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-8390-5510","authenticated-orcid":false,"given":"Gang","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wei","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yang","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2026,2,17]]},"reference":[{"key":"16_CR1","doi-asserted-by":"crossref","unstructured":"Azinovi\u0107, 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":"16_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":"16_CR3","doi-asserted-by":"crossref","unstructured":"Chen, S.E., Williams, L.: View interpolation for image synthesis. In: Seminal Graphics Papers: Pushing the Boundaries, vol. 2, pp. 423\u2013432 (2023)","DOI":"10.1145\/3596711.3596757"},{"key":"16_CR4","doi-asserted-by":"crossref","unstructured":"Deng, K., Liu, A., Zhu, J.Y., Ramanan, D.: Depth-supervised nerf: fewer views and faster training for free. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 12882\u201312891 (2022)","DOI":"10.1109\/CVPR52688.2022.01254"},{"key":"16_CR5","doi-asserted-by":"crossref","unstructured":"Fehn, C.: Depth-image-based rendering (dibr), compression, and transmission for a new approach on 3d-tv. In: Stereoscopic Displays and Virtual Reality Systems XI, vol.\u00a05291, pp. 93\u2013104. SPIE (2004)","DOI":"10.1117\/12.524762"},{"key":"16_CR6","doi-asserted-by":"crossref","unstructured":"Feng, M., Cheng, J., Jia, H., Liu, L., Xu, G., Yang, X.: Mc-stereo: multi-peak lookup and cascade search range for stereo matching. In: 2024 International Conference on 3D Vision (3DV), pp. 344\u2013353. IEEE (2024)","DOI":"10.1109\/3DV62453.2024.00083"},{"key":"16_CR7","doi-asserted-by":"crossref","unstructured":"Flynn, J., et al.: Deepview: high-quality view synthesis by learned gradient descent. In: Conference on Computer Vision and Pattern Recognition (CVPR), vol.\u00a03 (2019)","DOI":"10.1109\/CVPR.2019.00247"},{"key":"16_CR8","doi-asserted-by":"crossref","unstructured":"Flynn, J., Neulander, I., Philbin, J., Snavely, N.: Deepstereo: learning to predict new views from the world\u2019s imagery. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 5515\u20135524 (2016)","DOI":"10.1109\/CVPR.2016.595"},{"issue":"8","key":"16_CR9","doi-asserted-by":"publisher","first-page":"1362","DOI":"10.1109\/TPAMI.2009.161","volume":"32","author":"Y Furukawa","year":"2009","unstructured":"Furukawa, Y., Ponce, J.: Accurate, dense, and robust multiview stereopsis. IEEE Trans. Pattern Anal. Mach. Intell. 32(8), 1362\u20131376 (2009)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"16_CR10","doi-asserted-by":"crossref","unstructured":"Garbin, S.J., Kowalski, M., Johnson, M., Shotton, J., Valentin, J.: Fastnerf: high-fidelity neural rendering at 200fps. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 14346\u201314355 (2021)","DOI":"10.1109\/ICCV48922.2021.01408"},{"key":"16_CR11","doi-asserted-by":"crossref","unstructured":"Gupta, M., Yin, Q., Nayar, S.K.: Structured light in sunlight. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 545\u2013552 (2013)","DOI":"10.1109\/ICCV.2013.73"},{"key":"16_CR12","doi-asserted-by":"crossref","unstructured":"Hartley, R.: Multiple View Geometry in Computer Vision, vol.\u00a0665. Cambridge University Press (2003)","DOI":"10.1017\/CBO9780511811685"},{"key":"16_CR13","doi-asserted-by":"crossref","unstructured":"Hou, Y., Kannala, J., Solin, A.: Multi-view stereo by temporal nonparametric fusion. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 2651\u20132660 (2019)","DOI":"10.1109\/ICCV.2019.00274"},{"key":"16_CR14","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"471","DOI":"10.1007\/978-3-319-46493-0_29","volume-title":"Computer Vision \u2013 ECCV 2016","author":"T Kroeger","year":"2016","unstructured":"Kroeger, T., Timofte, R., Dai, D., Van Gool, L.: Fast optical flow using dense inverse search. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9908, pp. 471\u2013488. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46493-0_29"},{"key":"16_CR15","doi-asserted-by":"crossref","unstructured":"Levoy, M., Hanrahan, P.: Light field rendering. In: Seminal Graphics Papers: Pushing the Boundaries, vol. 2, pp. 441\u2013452 (2023)","DOI":"10.1145\/3596711.3596759"},{"key":"16_CR16","doi-asserted-by":"crossref","unstructured":"Li, Z., Niklaus, S., Snavely, N., Wang, O.: Neural scene flow fields for space-time view synthesis of dynamic scenes. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 6498\u20136508 (2021)","DOI":"10.1109\/CVPR46437.2021.00643"},{"key":"16_CR17","first-page":"15651","volume":"33","author":"L Liu","year":"2020","unstructured":"Liu, L., Gu, J., Zaw Lin, K., Chua, T.S., Theobalt, C.: Neural sparse voxel fields. Adv. Neural. Inf. Process. Syst. 33, 15651\u201315663 (2020)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"16_CR18","doi-asserted-by":"crossref","unstructured":"Liu, R., Yang, C., Sun, W., Wang, X., Li, H.: Stereogan: bridging synthetic-to-real domain gap by joint optimization of domain translation and stereo matching. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 12757\u201312766 (2020)","DOI":"10.1109\/CVPR42600.2020.01277"},{"key":"16_CR19","doi-asserted-by":"crossref","unstructured":"Lombardi, S., Simon, T., Saragih, J., Schwartz, G., Lehrmann, A., Sheikh, Y.: Neural volumes: learning dynamic renderable volumes from images. arXiv preprint arXiv:1906.07751 (2019)","DOI":"10.1145\/3306346.3323020"},{"key":"16_CR20","doi-asserted-by":"crossref","unstructured":"Martin-Brualla, R., Radwan, N., Sajjadi, M.S., Barron, J.T., Dosovitskiy, A., Duckworth, D.: Nerf in the wild: neural radiance fields for unconstrained photo collections. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 7210\u20137219 (2021)","DOI":"10.1109\/CVPR46437.2021.00713"},{"issue":"4","key":"16_CR21","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3306346.3322980","volume":"38","author":"B Mildenhall","year":"2019","unstructured":"Mildenhall, B., et al.: Local light field fusion: practical view synthesis with prescriptive sampling guidelines. ACM Trans. Graph. (ToG) 38(4), 1\u201314 (2019)","journal-title":"ACM Trans. Graph. (ToG)"},{"issue":"1","key":"16_CR22","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":"16_CR23","unstructured":"Ng, R., Levoy, M., Br\u00e9dif, M., Duval, G., Horowitz, M., Hanrahan, P.: Light field photography with a hand-held plenoptic camera. Ph.D. thesis, Stanford university (2005)"},{"key":"16_CR24","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":"16_CR25","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"},{"key":"16_CR26","unstructured":"Sitzmann, V., Zollh\u00f6fer, M., Wetzstein, G.: Scene representation networks: continuous 3D-structure-aware neural scene representations. In: Advances in Neural Information Processing Systems, vol. 32 (2019)"},{"key":"16_CR27","doi-asserted-by":"crossref","unstructured":"Sun, D., Yang, X., Liu, M.Y., Kautz, J.: Pwc-net: CNNs for optical flow using pyramid, warping, and cost volume. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 8934\u20138943 (2018)","DOI":"10.1109\/CVPR.2018.00931"},{"key":"16_CR28","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"402","DOI":"10.1007\/978-3-030-58536-5_24","volume-title":"Computer Vision \u2013 ECCV 2020","author":"Z Teed","year":"2020","unstructured":"Teed, Z., Deng, J.: RAFT: recurrent all-pairs field transforms for optical flow. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, J.-M. (eds.) ECCV 2020. LNCS, vol. 12347, pp. 402\u2013419. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-58536-5_24"},{"issue":"2","key":"16_CR29","doi-asserted-by":"publisher","first-page":"606","DOI":"10.1109\/JSTARS.2017.2781132","volume":"11","author":"R Wang","year":"2018","unstructured":"Wang, R., Peethambaran, J., Chen, D.: Lidar point clouds to 3-D urban models: a review. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 11(2), 606\u2013627 (2018)","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"16_CR30","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"},{"issue":"12","key":"16_CR31","doi-asserted-by":"publisher","first-page":"123601","DOI":"10.1117\/1.3516729","volume":"45","author":"S Zhang","year":"2006","unstructured":"Zhang, S., Huang, P.S.: High-resolution, real-time three-dimensional shape measurement. Opt. Eng. 45(12), 123601 (2006)","journal-title":"Opt. Eng."},{"key":"16_CR32","doi-asserted-by":"crossref","unstructured":"Zhou, T., Tucker, R., Flynn, J., Fyffe, G., Snavely, N.: Stereo magnification: learning view synthesis using multiplane images. arXiv preprint arXiv:1805.09817 (2018)","DOI":"10.1145\/3197517.3201323"}],"container-title":["Lecture Notes in Computer Science","MultiMedia Modeling"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-95-6950-2_16","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,16]],"date-time":"2026-02-16T11:59:46Z","timestamp":1771243186000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-95-6950-2_16"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"ISBN":["9789819569496","9789819569502"],"references-count":32,"URL":"https:\/\/doi.org\/10.1007\/978-981-95-6950-2_16","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":"17 February 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"MMM","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Multimedia Modeling","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Prague","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Czech Republic","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2026","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29 January 2026","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"31 January 2026","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"32","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"mmm2026","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/mmm2026.cz\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}