{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T08:26:23Z","timestamp":1743063983857,"version":"3.40.3"},"publisher-location":"Cham","reference-count":26,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031500718"},{"type":"electronic","value":"9783031500725"}],"license":[{"start":{"date-parts":[[2023,12,29]],"date-time":"2023-12-29T00:00:00Z","timestamp":1703808000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,12,29]],"date-time":"2023-12-29T00:00:00Z","timestamp":1703808000000},"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":[[2024]]},"DOI":"10.1007\/978-3-031-50072-5_16","type":"book-chapter","created":{"date-parts":[[2023,12,28]],"date-time":"2023-12-28T08:02:17Z","timestamp":1703750537000},"page":"199-210","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Point Cloud Rendering via\u00a0Multi-plane NeRF"],"prefix":"10.1007","author":[{"given":"Dongmei","family":"Ma","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Juan","family":"Cao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9960-4896","authenticated-orcid":false,"given":"Zhonggui","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,12,29]]},"reference":[{"key":"16_CR1","doi-asserted-by":"publisher","first-page":"35105","DOI":"10.1007\/s11042-020-09303-9","volume":"80","author":"SG Ali","year":"2021","unstructured":"Ali, S.G., et al.: Cost-effective broad learning-based ultrasound biomicroscopy with 3D reconstruction for ocular anterior segmentation. Multimed. Tools Appl. 80, 35105\u201335122 (2021)","journal-title":"Multimed. Tools Appl."},{"key":"16_CR2","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"696","DOI":"10.1007\/978-3-030-58542-6_42","volume-title":"Computer Vision \u2013 ECCV 2020","author":"K-A Aliev","year":"2020","unstructured":"Aliev, K.-A., Sevastopolsky, A., Kolos, M., Ulyanov, D., Lempitsky, V.: Neural point-based graphics. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, J.-M. (eds.) ECCV 2020, Part XXII. LNCS, vol. 12367, pp. 696\u2013712. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-58542-6_42"},{"key":"16_CR3","doi-asserted-by":"publisher","first-page":"829","DOI":"10.1007\/s00371-018-1550-6","volume":"34","author":"G Bui","year":"2018","unstructured":"Bui, G., Le, T., Morago, B., Duan, Y.: Point-based rendering enhancement via deep learning. Vis. Comput. 34, 829\u2013841 (2018)","journal-title":"Vis. Comput."},{"key":"16_CR4","doi-asserted-by":"crossref","unstructured":"Chen, A., et al.: MVSNeRF: fast generalizable radiance field reconstruction from multi-view stereo. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 14124\u201314133 (2021)","DOI":"10.1109\/ICCV48922.2021.01386"},{"key":"16_CR5","doi-asserted-by":"crossref","unstructured":"Dai, A., Chang, A.X., Savva, M., Halber, M., Funkhouser, T., Nie\u00dfner, M.: ScanNet: richly-annotated 3D reconstructions of indoor scenes. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 5828\u20135839 (2017)","DOI":"10.1109\/CVPR.2017.261"},{"key":"16_CR6","doi-asserted-by":"crossref","unstructured":"Dai, P., Zhang, Y., Li, Z., Liu, S., Zeng, B.: Neural point cloud rendering via multi-plane projection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 7830\u20137839 (2020)","DOI":"10.1109\/CVPR42600.2020.00785"},{"key":"16_CR7","unstructured":"Ha, D., Dai, A., Le, Q.V.: Hypernetworks. arXiv preprint arXiv:1609.09106 (2016)"},{"key":"16_CR8","doi-asserted-by":"crossref","unstructured":"Huang, X., Zhang, Y., Ni, B., Li, T., Chen, K., Zhang, W.: Boosting point clouds rendering via radiance mapping. arXiv preprint arXiv:2210.15107 (2022)","DOI":"10.1609\/aaai.v37i1.25175"},{"issue":"4","key":"16_CR9","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3072959.3073659","volume":"36","author":"S Iizuka","year":"2017","unstructured":"Iizuka, S., Simo-Serra, E., Ishikawa, H.: Globally and locally consistent image completion. ACM Trans. Graph. (TOG) 36(4), 1\u201314 (2017)","journal-title":"ACM Trans. Graph. (TOG)"},{"key":"16_CR10","doi-asserted-by":"crossref","unstructured":"Jensen, R., Dahl, A., Vogiatzis, G., Tola, E., Aan\u00e6s, H.: Large scale multi-view stereopsis evaluation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 406\u2013413 (2014)","DOI":"10.1109\/CVPR.2014.59"},{"key":"16_CR11","doi-asserted-by":"crossref","unstructured":"Kopanas, G., Philip, J., Leimk\u00fchler, T., Drettakis, G.: Point-based neural rendering with per-view optimization. In: Computer Graphics Forum, vol. 40, pp. 29\u201343. Wiley Online Library (2021)","DOI":"10.1111\/cgf.14339"},{"issue":"1","key":"16_CR12","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_CR13","doi-asserted-by":"crossref","unstructured":"M\u00fcller, T., Evans, A., Schied, C., Keller, A.: Instant neural graphics primitives with a multiresolution hash encoding. ACM Trans. Graph. 41(4), 102:1\u2013102:15 (2022)","DOI":"10.1145\/3528223.3530127"},{"key":"16_CR14","doi-asserted-by":"crossref","unstructured":"Qiu, J., Yin, Z.X., Cheng, M.M., Ren, B.: Rendering real-world unbounded scenes with cars by learning positional bias. Vis. Comput. 1\u201314 (2023)","DOI":"10.1007\/s00371-023-03070-y"},{"key":"16_CR15","doi-asserted-by":"crossref","unstructured":"Qiu, J., Zhu, Y., Jiang, P.T., Cheng, M.M., Ren, B.: RdNeRF: relative depth guided nerf for dense free view synthesis. Vis. Comput. 1\u201313 (2023)","DOI":"10.1007\/s00371-023-02863-5"},{"key":"16_CR16","doi-asserted-by":"crossref","unstructured":"Rakhimov, R., Ardelean, A.T., Lempitsky, V., Burnaev, E.: NPBG++: accelerating neural point-based graphics. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 15969\u201315979 (2022)","DOI":"10.1109\/CVPR52688.2022.01550"},{"issue":"4","key":"16_CR17","first-page":"1","volume":"41","author":"D R\u00fcckert","year":"2022","unstructured":"R\u00fcckert, D., Franke, L., Stamminger, M.: ADOP: approximate differentiable one-pixel point rendering. ACM Trans. Graph. (TOG) 41(4), 1\u201314 (2022)","journal-title":"ACM Trans. Graph. (TOG)"},{"key":"16_CR18","doi-asserted-by":"crossref","unstructured":"Thalmann, N., Kim, J., Papagiannakis, G., Thalmann, D., Sheng, B.: Computer graphics for metaverse. Virtual Reality Intell. Hardw. 4, ii\u2013iv (10 2022)","DOI":"10.1016\/j.vrih.2022.10.001"},{"key":"16_CR19","unstructured":"Vaswani, A., et al.: Attention is all you need. In: Advances in Neural Information Processing Systems, vol. 30 (2017)"},{"issue":"6","key":"16_CR20","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3355089.3356513","volume":"38","author":"Y Wang","year":"2019","unstructured":"Wang, Y., Serena, F., Wu, S., \u00d6ztireli, C., Sorkine-Hornung, O.: Differentiable surface splatting for point-based geometry processing. ACM Trans. Graph. 38(6), 1\u201314 (2019)","journal-title":"ACM Trans. Graph."},{"key":"16_CR21","doi-asserted-by":"crossref","unstructured":"Wiles, O., Gkioxari, G., Szeliski, R., Johnson, J.: SynSin: end-to-end view synthesis from a single image. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 7467\u20137477 (2020)","DOI":"10.1109\/CVPR42600.2020.00749"},{"key":"16_CR22","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":"16_CR23","doi-asserted-by":"crossref","unstructured":"Yao, Y., Luo, Z., Li, S., Fang, T., Quan, L.: MVSNet: depth inference for unstructured multi-view stereo. In: Proceedings of the European Conference on Computer Vision (ECCV), pp. 767\u2013783 (2018)","DOI":"10.1007\/978-3-030-01237-3_47"},{"key":"16_CR24","doi-asserted-by":"crossref","unstructured":"Yu, A., Ye, V., Tancik, M., Kanazawa, A.: pixelNeRF: neural radiance fields from one or few images. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 4578\u20134587 (2021)","DOI":"10.1109\/CVPR46437.2021.00455"},{"key":"16_CR25","doi-asserted-by":"crossref","unstructured":"Zhang, Q., Baek, S.H., Rusinkiewicz, S., Heide, F.: Differentiable point-based radiance fields for efficient view synthesis. arXiv preprint arXiv:2205.14330 (2022)","DOI":"10.1145\/3550469.3555413"},{"key":"16_CR26","unstructured":"Zimny, D., Trzci\u0144ski, T., Spurek, P.: Points2NeRF: generating neural radiance fields from 3D point cloud. arXiv preprint arXiv:2206.01290 (2022)"}],"container-title":["Lecture Notes in Computer Science","Advances in Computer Graphics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-50072-5_16","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,12,28]],"date-time":"2023-12-28T08:05:33Z","timestamp":1703750733000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-50072-5_16"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,12,29]]},"ISBN":["9783031500718","9783031500725"],"references-count":26,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-50072-5_16","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2023,12,29]]},"assertion":[{"value":"29 December 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"CGI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Computer Graphics International Conference","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":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28 August 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"1 September 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"cgi2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"385","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"149","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"39% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}