{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,6]],"date-time":"2026-06-06T17:04:45Z","timestamp":1780765485282,"version":"3.54.1"},"publisher-location":"Cham","reference-count":38,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031200700","type":"print"},{"value":"9783031200717","type":"electronic"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-031-20071-7_14","type":"book-chapter","created":{"date-parts":[[2022,11,12]],"date-time":"2022-11-12T05:15:09Z","timestamp":1668230109000},"page":"233-249","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Bringing Rolling Shutter Images Alive with\u00a0Dual Reversed Distortion"],"prefix":"10.1007","author":[{"given":"Zhihang","family":"Zhong","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mingdeng","family":"Cao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiao","family":"Sun","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhirong","family":"Wu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhongyi","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yinqiang","family":"Zheng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stephen","family":"Lin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Imari","family":"Sato","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2022,11,13]]},"reference":[{"key":"14_CR1","doi-asserted-by":"crossref","unstructured":"Albl, C., Kukelova, Z., Larsson, V., Polic, M., Pajdla, T., Schindler, K.: From two rolling shutters to one global shutter. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 2505\u20132513 (2020)","DOI":"10.1109\/CVPR42600.2020.00258"},{"key":"14_CR2","doi-asserted-by":"crossref","unstructured":"Baker, S., Bennett, E., Kang, S.B., Szeliski, R.: Removing rolling shutter wobble. In: 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 2392\u20132399. IEEE (2010)","DOI":"10.1109\/CVPR.2010.5539932"},{"key":"14_CR3","doi-asserted-by":"crossref","unstructured":"Bao, W., Lai, W.S., Ma, C., Zhang, X., Gao, Z., Yang, M.H.: Depth-aware video frame interpolation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 3703\u20133712 (2019)","DOI":"10.1109\/CVPR.2019.00382"},{"key":"14_CR4","doi-asserted-by":"crossref","unstructured":"Choi, M., Kim, H., Han, B., Xu, N., Lee, K.M.: Channel attention is all you need for video frame interpolation. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 34, pp. 10663\u201310671 (2020)","DOI":"10.1609\/aaai.v34i07.6693"},{"key":"14_CR5","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":"14_CR6","doi-asserted-by":"crossref","unstructured":"Dosovitskiy, A., et al.: Flownet: learning optical flow with convolutional networks. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 2758\u20132766 (2015)","DOI":"10.1109\/ICCV.2015.316"},{"key":"14_CR7","doi-asserted-by":"crossref","unstructured":"Fan, B., Dai, Y.: Inverting a rolling shutter camera: bring rolling shutter images to high framerate global shutter video. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 4228\u20134237 (2021)","DOI":"10.1109\/ICCV48922.2021.00419"},{"key":"14_CR8","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":"14_CR9","doi-asserted-by":"crossref","unstructured":"Forss\u00e9n, P.E., Ringaby, E.: Rectifying rolling shutter video from hand-held devices. In: 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 507\u2013514. IEEE (2010)","DOI":"10.1109\/CVPR.2010.5540173"},{"key":"14_CR10","doi-asserted-by":"crossref","unstructured":"Grundmann, M., Kwatra, V., Castro, D., Essa, I.: Calibration-free rolling shutter removal. In: 2012 IEEE International Conference on Computational Photography (ICCP), pp. 1\u20138. IEEE (2012)","DOI":"10.1109\/ICCPhot.2012.6215213"},{"key":"14_CR11","unstructured":"Huang, Z., Zhang, T., Heng, W., Shi, B., Zhou, S.: Rife: real-time intermediate flow estimation for video frame interpolation. arXiv preprint arXiv:2011.06294 (2020)"},{"key":"14_CR12","doi-asserted-by":"crossref","unstructured":"Ilg, E., Mayer, N., Saikia, T., Keuper, M., Dosovitskiy, A., Brox, T.: Flownet 2.0: evolution of optical flow estimation with deep networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 2462\u20132470 (2017)","DOI":"10.1109\/CVPR.2017.179"},{"key":"14_CR13","doi-asserted-by":"crossref","unstructured":"Jiang, H., Sun, D., Jampani, V., Yang, M.H., Learned-Miller, E., Kautz, J.: Super slomo: high quality estimation of multiple intermediate frames for video interpolation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 9000\u20139008 (2018)","DOI":"10.1109\/CVPR.2018.00938"},{"key":"14_CR14","doi-asserted-by":"crossref","unstructured":"Jin, M., Hu, Z., Favaro, P.: Learning to extract flawless slow motion from blurry videos. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 8112\u20138121 (2019)","DOI":"10.1109\/CVPR.2019.00830"},{"key":"14_CR15","doi-asserted-by":"crossref","unstructured":"Jin, M., Meishvili, G., Favaro, P.: Learning to extract a video sequence from a single motion-blurred image. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 6334\u20136342 (2018)","DOI":"10.1109\/CVPR.2018.00663"},{"key":"14_CR16","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"694","DOI":"10.1007\/978-3-319-46475-6_43","volume-title":"Computer Vision \u2013 ECCV 2016","author":"J Johnson","year":"2016","unstructured":"Johnson, J., Alahi, A., Fei-Fei, L.: Perceptual losses for real-time style transfer and super-resolution. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9906, pp. 694\u2013711. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46475-6_43"},{"key":"14_CR17","unstructured":"Kalluri, T., Pathak, D., Chandraker, M., Tran, D.: Flavr: flow-agnostic video representations for fast frame interpolation. arXiv preprint arXiv:2012.08512 (2020)"},{"key":"14_CR18","doi-asserted-by":"crossref","unstructured":"Lin, S., et al.: Learning event-driven video deblurring and interpolation. In: European Conference on Computer Vision, vol. 3 (2020)","DOI":"10.1007\/978-3-030-58598-3_41"},{"issue":"1","key":"14_CR19","first-page":"154","volume":"35","author":"D Litwiller","year":"2001","unstructured":"Litwiller, D.: CCD vs. CMOS. Photonics Spectra 35(1), 154\u2013158 (2001)","journal-title":"Photonics Spectra"},{"key":"14_CR20","doi-asserted-by":"crossref","unstructured":"Liu, P., Cui, Z., Larsson, V., Pollefeys, M.: Deep shutter unrolling network. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 5941\u20135949 (2020)","DOI":"10.1109\/CVPR42600.2020.00598"},{"key":"14_CR21","unstructured":"Loshchilov, I., Hutter, F.: Decoupled weight decay regularization. arXiv preprint arXiv:1711.05101 (2017)"},{"key":"14_CR22","doi-asserted-by":"crossref","unstructured":"Nah, S., Hyun Kim, T., Mu Lee, K.: Deep multi-scale convolutional neural network for dynamic scene deblurring. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3883\u20133891 (2017)","DOI":"10.1109\/CVPR.2017.35"},{"key":"14_CR23","doi-asserted-by":"crossref","unstructured":"Niklaus, S., Liu, F.: Softmax splatting for video frame interpolation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 5437\u20135446 (2020)","DOI":"10.1109\/CVPR42600.2020.00548"},{"key":"14_CR24","doi-asserted-by":"crossref","unstructured":"Oth, L., Furgale, P., Kneip, L., Siegwart, R.: Rolling shutter camera calibration. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1360\u20131367 (2013)","DOI":"10.1109\/CVPR.2013.179"},{"key":"14_CR25","doi-asserted-by":"crossref","unstructured":"Pan, L., Scheerlinck, C., Yu, X., Hartley, R., Liu, M., Dai, Y.: Bringing a blurry frame alive at high frame-rate with an event camera. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 6820\u20136829 (2019)","DOI":"10.1109\/CVPR.2019.00698"},{"key":"14_CR26","unstructured":"Paszke, A., et al.: Pytorch: an imperative style, high-performance deep learning library. arXiv preprint arXiv:1912.01703 (2019)"},{"key":"14_CR27","doi-asserted-by":"crossref","unstructured":"Purkait, P., Zach, C., Leonardis, A.: Rolling shutter correction in manhattan world. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 882\u2013890 (2017)","DOI":"10.1109\/ICCV.2017.101"},{"key":"14_CR28","doi-asserted-by":"crossref","unstructured":"Purohit, K., Shah, A., Rajagopalan, A.: Bringing alive blurred moments. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 6830\u20136839 (2019)","DOI":"10.1109\/CVPR.2019.00699"},{"key":"14_CR29","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":"14_CR30","doi-asserted-by":"crossref","unstructured":"Rengarajan, V., Rajagopalan, A.N., Aravind, R.: From bows to arrows: rolling shutter rectification of urban scenes. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 2773\u20132781 (2016)","DOI":"10.1109\/CVPR.2016.303"},{"key":"14_CR31","doi-asserted-by":"crossref","unstructured":"Shen, W., Bao, W., Zhai, G., Chen, L., Min, X., Gao, Z.: Blurry video frame interpolation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 5114\u20135123 (2020)","DOI":"10.1109\/CVPR42600.2020.00516"},{"key":"14_CR32","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":"14_CR33","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"},{"key":"14_CR34","doi-asserted-by":"crossref","unstructured":"Vasu, S., Rajagopalan, A., et al.: Occlusion-aware rolling shutter rectification of 3D scenes. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 636\u2013645 (2018)","DOI":"10.1109\/CVPR.2018.00073"},{"key":"14_CR35","doi-asserted-by":"crossref","unstructured":"Yang, X., Xiang, W., Zeng, H., Zhang, L.: Real-world video super-resolution: a benchmark dataset and a decomposition based learning scheme. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 4781\u20134790 (2021)","DOI":"10.1109\/ICCV48922.2021.00474"},{"key":"14_CR36","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"191","DOI":"10.1007\/978-3-030-58539-6_12","volume-title":"Computer Vision \u2013 ECCV 2020","author":"Z Zhong","year":"2020","unstructured":"Zhong, Z., Gao, Y., Zheng, Y., Zheng, B.: Efficient spatio-temporal recurrent neural network for video deblurring. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, J.-M. (eds.) ECCV 2020. LNCS, vol. 12351, pp. 191\u2013207. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-58539-6_12"},{"key":"14_CR37","doi-asserted-by":"crossref","unstructured":"Zhuang, B., Cheong, L.F., Hee Lee, 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"},{"key":"14_CR38","doi-asserted-by":"crossref","unstructured":"Zhuang, B., Tran, Q.H., Ji, P., Cheong, L.F., Chandraker, M.: Learning structure-and-motion-aware rolling shutter correction. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 4551\u20134560 (2019)","DOI":"10.1109\/CVPR.2019.00468"}],"container-title":["Lecture Notes in Computer Science","Computer Vision \u2013 ECCV 2022"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-20071-7_14","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,11,12]],"date-time":"2022-11-12T05:22:15Z","timestamp":1668230535000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-20071-7_14"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031200700","9783031200717"],"references-count":38,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-20071-7_14","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"13 November 2022","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":"Tel Aviv","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Israel","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23 October 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27 October 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"eccv2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/eccv2022.ecva.net\/","order":11,"name":"conference_url","label":"Conference URL","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":"CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"5804","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":"1645","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":"28% - 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":"3.21","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":"3.91","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)"}}]}}