{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T04:58:35Z","timestamp":1742965115530,"version":"3.40.3"},"publisher-location":"Cham","reference-count":40,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031727603"},{"type":"electronic","value":"9783031727610"}],"license":[{"start":{"date-parts":[[2024,9,30]],"date-time":"2024-09-30T00:00:00Z","timestamp":1727654400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,9,30]],"date-time":"2024-09-30T00:00:00Z","timestamp":1727654400000},"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\/978-3-031-72761-0_26","type":"book-chapter","created":{"date-parts":[[2024,9,29]],"date-time":"2024-09-29T07:01:50Z","timestamp":1727593310000},"page":"458-475","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["URS-NeRF: Unordered Rolling Shutter Bundle Adjustment for\u00a0Neural Radiance Fields"],"prefix":"10.1007","author":[{"given":"Bo","family":"Xu","sequence":"first","affiliation":[]},{"given":"Ziao","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Mengqi","family":"Guo","sequence":"additional","affiliation":[]},{"given":"Jiancheng","family":"Li","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1583-0475","authenticated-orcid":false,"given":"Gim Hee","family":"Lee","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,9,30]]},"reference":[{"key":"26_CR1","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"36","DOI":"10.1007\/978-3-319-46454-1_3","volume-title":"Computer Vision \u2013 ECCV 2016","author":"C Albl","year":"2016","unstructured":"Albl, C., Sugimoto, A., Pajdla, T.: Degeneracies in rolling shutter SfM. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9909, pp. 36\u201351. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46454-1_3"},{"key":"26_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":"26_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":"26_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. arXiv preprint arXiv:2304.06706 (2023)","DOI":"10.1109\/ICCV51070.2023.01804"},{"key":"26_CR5","doi-asserted-by":"publisher","first-page":"50771","DOI":"10.1109\/ACCESS.2020.2978589","volume":"8","author":"L Cao","year":"2020","unstructured":"Cao, L., Ling, J., Xiao, X.: The WHU rolling shutter visual-inertial dataset. IEEE Access 8, 50771\u201350779 (2020)","journal-title":"IEEE Access"},{"key":"26_CR6","series-title":"LNCS","doi-asserted-by":"publisher","first-page":"333","DOI":"10.1007\/978-3-031-19824-3_20","volume-title":"ECCV 2022","author":"A Chen","year":"2022","unstructured":"Chen, A., Xu, Z., Geiger, A., Yu, J., Su, H.: TensoRF: tensorial radiance fields. In: Avidan, S., Brostow, G., Ciss\u00e9, M., Farinella, G.M., Hassner, T. (eds.) ECCV 2022. LNCS, vol. 13692, pp. 333\u2013350. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-19824-3_20"},{"key":"26_CR7","doi-asserted-by":"crossref","unstructured":"Chen, Y., Lee, G.H.: DBARF: deep bundle-adjusting generalizable neural radiance fields. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 24\u201334 (2023)","DOI":"10.1109\/CVPR52729.2023.00011"},{"key":"26_CR8","doi-asserted-by":"crossref","unstructured":"Dai, Y., Li, H., Kneip, L.: Rolling shutter camera relative pose: generalized epipolar geometry. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 4132\u20134140 (2016)","DOI":"10.1109\/CVPR.2016.448"},{"key":"26_CR9","doi-asserted-by":"crossref","unstructured":"DeTone, D., Malisiewicz, T., Rabinovich, A.: SuperPoint: self-supervised interest point detection and description. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp. 224\u2013236 (2018)","DOI":"10.1109\/CVPRW.2018.00060"},{"key":"26_CR10","doi-asserted-by":"crossref","unstructured":"Doll\u00e1r, P., Welinder, P., Perona, P.: Cascaded pose regression. In: 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 1078\u20131085. IEEE (2010)","DOI":"10.1109\/CVPR.2010.5540094"},{"key":"26_CR11","doi-asserted-by":"crossref","unstructured":"Fan, B., Dai, Y., He, M.: Sunet: symmetric undistortion network for rolling shutter correction. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 4541\u20134550 (2021)","DOI":"10.1109\/ICCV48922.2021.00450"},{"key":"26_CR12","doi-asserted-by":"crossref","unstructured":"Fan, B., Dai, Y., Zhang, Z., Liu, Q., He, M.: Context-aware video reconstruction for rolling shutter cameras. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 17572\u201317582 (2022)","DOI":"10.1109\/CVPR52688.2022.01705"},{"key":"26_CR13","doi-asserted-by":"crossref","unstructured":"Fu, H., Yu, X., Li, L., Zhang, L.: CBARF: cascaded bundle-adjusting neural radiance fields from imperfect camera poses. arXiv preprint arXiv:2310.09776 (2023)","DOI":"10.1109\/TMM.2024.3388929"},{"key":"26_CR14","doi-asserted-by":"crossref","unstructured":"Hedborg, J., Forss\u00e9n, P.E., Felsberg, M., Ringaby, E.: Rolling shutter bundle adjustment. In: 2012 IEEE Conference on Computer Vision and Pattern Recognition, pp. 1434\u20131441. IEEE (2012)","DOI":"10.1109\/CVPR.2012.6247831"},{"key":"26_CR15","doi-asserted-by":"crossref","unstructured":"Hu, W., et al.: Tri-MipRF: Tri-Mip representation for efficient anti-aliasing neural radiance fields. In: ICCV (2023)","DOI":"10.1109\/ICCV51070.2023.01811"},{"issue":"13","key":"26_CR16","doi-asserted-by":"publisher","first-page":"800","DOI":"10.1049\/el:20080522","volume":"44","author":"Q Huynh-Thu","year":"2008","unstructured":"Huynh-Thu, Q., Ghanbari, M.: Scope of validity of PSNR in image\/video quality assessment. Electron. Lett. 44(13), 800\u2013801 (2008)","journal-title":"Electron. Lett."},{"issue":"4","key":"26_CR17","doi-asserted-by":"publisher","first-page":"775","DOI":"10.1109\/TPAMI.2018.2819679","volume":"41","author":"S Im","year":"2018","unstructured":"Im, S., Ha, H., Choe, G., Jeon, H.G., Joo, K., Kweon, I.S.: Accurate 3D reconstruction from small motion clip for rolling shutter cameras. IEEE Trans. Pattern Anal. Mach. Intell. 41(4), 775\u2013787 (2018)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"26_CR18","doi-asserted-by":"crossref","unstructured":"Jarrett, K., Kavukcuoglu, K., Ranzato, M., LeCun, Y.: What is the best multi-stage architecture for object recognition? In: 2009 IEEE 12th International Conference on Computer Vision, pp. 2146\u20132153. IEEE (2009)","DOI":"10.1109\/ICCV.2009.5459469"},{"issue":"4","key":"26_CR19","doi-asserted-by":"publisher","first-page":"386","DOI":"10.1016\/j.vrih.2019.07.002","volume":"1","author":"L Jinyu","year":"2019","unstructured":"Jinyu, L., Bangbang, Y., Danpeng, C., Nan, W., Guofeng, Z., Hujun, B.: Survey and evaluation of monocular visual-inertial slam algorithms for augmented reality. Virtual Reality Intell. Hardware 1(4), 386\u2013410 (2019)","journal-title":"Virtual Reality Intell. Hardware"},{"key":"26_CR20","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.patrec.2018.04.004","volume":"111","author":"Y Lao","year":"2018","unstructured":"Lao, Y., Ait-Aider, O., Araujo, H.: Robustified structure from motion with rolling-shutter camera using straightness constraint. Pattern Recogn. Lett. 111, 1\u20138 (2018)","journal-title":"Pattern Recogn. Lett."},{"key":"26_CR21","doi-asserted-by":"publisher","first-page":"100","DOI":"10.1007\/s11263-020-01368-1","volume":"129","author":"Y Lao","year":"2021","unstructured":"Lao, Y., Ait-Aider, O., Bartoli, A.: Solving rolling shutter 3D vision problems using analogies with non-rigidity. Int. J. Comput. Vis. 129, 100\u2013122 (2021)","journal-title":"Int. J. Comput. Vis."},{"key":"26_CR22","doi-asserted-by":"crossref","unstructured":"Li, M., Wang, P., Zhao, L., Liao, B., Liu, P.: USB-NeRF: unrolling shutter bundle adjusted neural radiance fields. arXiv preprint arXiv:2310.02687 (2023)","DOI":"10.1109\/CVPR52729.2023.00406"},{"key":"26_CR23","doi-asserted-by":"crossref","unstructured":"Liao, B., Qu, D., Xue, Y., Zhang, H., Lao, Y.: Revisiting rolling shutter bundle adjustment: toward accurate and fast solution. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 4863\u20134871 (2023)","DOI":"10.1109\/CVPR52729.2023.00471"},{"key":"26_CR24","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":"26_CR25","unstructured":"Meingast, M., Geyer, C., Sastry, S.: Geometric models of rolling-shutter cameras. arXiv preprint cs\/0503076 (2005)"},{"issue":"4","key":"26_CR26","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":"26_CR27","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":"26_CR28","doi-asserted-by":"publisher","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). https:\/\/doi.org\/10.1145\/3528223.3530127","DOI":"10.1145\/3528223.3530127"},{"issue":"4","key":"26_CR29","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)"},{"issue":"3","key":"26_CR30","doi-asserted-by":"publisher","first-page":"208","DOI":"10.1007\/s11263-015-0811-3","volume":"113","author":"A Patron-Perez","year":"2015","unstructured":"Patron-Perez, A., Lovegrove, S., Sibley, G.: A spline-based trajectory representation for sensor fusion and rolling shutter cameras. Int. J. Comput. Vis. 113(3), 208\u2013219 (2015)","journal-title":"Int. J. Comput. Vis."},{"key":"26_CR31","doi-asserted-by":"crossref","unstructured":"Rengarajan, V., Balaji, Y., Rajagopalan, A.: Unrolling the shutter: CNN to correct motion distortions. In: Proceedings of the IEEE Conference on computer Vision and Pattern Recognition, pp. 2291\u20132299 (2017)","DOI":"10.1109\/CVPR.2017.252"},{"key":"26_CR32","doi-asserted-by":"crossref","unstructured":"Sarlin, P.E., DeTone, D., Malisiewicz, T., Rabinovich, A.: Superglue: learning feature matching with graph neural networks. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 4938\u20134947 (2020)","DOI":"10.1109\/CVPR42600.2020.00499"},{"key":"26_CR33","doi-asserted-by":"crossref","unstructured":"Saurer, O., Pollefeys, M., Lee, G.H.: Sparse to dense 3D reconstruction from rolling shutter images. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3337\u20133345 (2016)","DOI":"10.1109\/CVPR.2016.363"},{"key":"26_CR34","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":"26_CR35","unstructured":"Song, L., Wang, G., Liu, J., Fu, Z., Miao, Y., et\u00a0al.: SC-NeRF: self-correcting neural radiance field with sparse views. arXiv preprint arXiv:2309.05028 (2023)"},{"issue":"4","key":"26_CR36","doi-asserted-by":"publisher","first-page":"600","DOI":"10.1109\/TIP.2003.819861","volume":"13","author":"Z Wang","year":"2004","unstructured":"Wang, Z., Bovik, A.C., Sheikh, H.R., Simoncelli, E.P.: Image quality assessment: from error visibility to structural similarity. IEEE Trans. Image Process. 13(4), 600\u2013612 (2004)","journal-title":"IEEE Trans. Image Process."},{"key":"26_CR37","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":"26_CR38","doi-asserted-by":"crossref","unstructured":"Zamir, S.W., et al.: Multi-stage progressive image restoration. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 14821\u201314831 (2021)","DOI":"10.1109\/CVPR46437.2021.01458"},{"key":"26_CR39","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":"26_CR40","doi-asserted-by":"crossref","unstructured":"Zhuang, B., Cheong, L.F., Hee\u00a0Lee, G.: Rolling-shutter-aware differential SFM and image rectification. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 948\u2013956 (2017)","DOI":"10.1109\/ICCV.2017.108"}],"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\/978-3-031-72761-0_26","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,29]],"date-time":"2024-09-29T07:35:48Z","timestamp":1727595348000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-72761-0_26"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,9,30]]},"ISBN":["9783031727603","9783031727610"],"references-count":40,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-72761-0_26","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024,9,30]]},"assertion":[{"value":"30 September 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"}}]}}