{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,9]],"date-time":"2026-05-09T04:04:11Z","timestamp":1778299451812,"version":"3.51.4"},"publisher-location":"Cham","reference-count":58,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031729423","type":"print"},{"value":"9783031729430","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,11,29]],"date-time":"2024-11-29T00:00:00Z","timestamp":1732838400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,11,29]],"date-time":"2024-11-29T00:00:00Z","timestamp":1732838400000},"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\/978-3-031-72943-0_1","type":"book-chapter","created":{"date-parts":[[2024,11,28]],"date-time":"2024-11-28T13:40:53Z","timestamp":1732801253000},"page":"1-19","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["CMTA: Cross-Modal Temporal Alignment for\u00a0Event-Guided Video Deblurring"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8608-9514","authenticated-orcid":false,"given":"Taewoo","family":"Kim","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0896-6793","authenticated-orcid":false,"given":"Hoonhee","family":"Cho","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1634-2756","authenticated-orcid":false,"given":"Kuk-Jin","family":"Yoon","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,11,29]]},"reference":[{"key":"1_CR1","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"748","DOI":"10.1007\/978-3-030-01237-3_45","volume-title":"Computer Vision \u2013 ECCV 2018","author":"M Aittala","year":"2018","unstructured":"Aittala, M., Durand, F.: Burst image deblurring using permutation invariant convolutional neural networks. In: Ferrari, V., Hebert, M., Sminchisescu, C., Weiss, Y. (eds.) ECCV 2018. LNCS, vol. 11212, pp. 748\u2013764. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-01237-3_45"},{"issue":"10","key":"1_CR2","doi-asserted-by":"publisher","first-page":"2333","DOI":"10.1109\/JSSC.2014.2342715","volume":"49","author":"C Brandli","year":"2014","unstructured":"Brandli, C., Berner, R., Yang, M., Liu, S.C., Delbruck, T.: A 240$$\\times $$ 180 130 db 3 $$\\mu $$s latency global shutter spatiotemporal vision sensor. IEEE J. Solid-State Circuits 49(10), 2333\u20132341 (2014)","journal-title":"IEEE J. Solid-State Circuits"},{"key":"1_CR3","doi-asserted-by":"crossref","unstructured":"Cao, M., Zhong, Z., Wang, J., Zheng, Y., Yang, Y.: Learning adaptive warping for real-world rolling shutter correction. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 17785\u201317793 (2022)","DOI":"10.1109\/CVPR52688.2022.01726"},{"key":"1_CR4","doi-asserted-by":"crossref","unstructured":"Chan, K.C., Wang, X., Yu, K., Dong, C., Loy, C.C.: Basicvsr: the search for essential components in video super-resolution and beyond. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2021)","DOI":"10.1109\/CVPR46437.2021.00491"},{"key":"1_CR5","doi-asserted-by":"crossref","unstructured":"Chan, K.C., Zhou, S., Xu, X., Loy, C.C.: Basicvsr++: improving video super-resolution with enhanced propagation and alignment (2021)","DOI":"10.1109\/CVPR52688.2022.00588"},{"key":"1_CR6","doi-asserted-by":"publisher","unstructured":"Chen, L., Chu, X., Zhang, X., Sun, J.: Simple baselines for image restoration. In: Avidan, S., Brostow, G., Ciss\u00e9, M., Farinella, G.M., Hassner, T. (eds.) ECCV 2022. LNCS, vol. 13667, pp. 17\u201333. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-20071-7_2","DOI":"10.1007\/978-3-031-20071-7_2"},{"key":"1_CR7","unstructured":"Chen, S., Zhang, J., Zheng, Y., Huang, T., Yu, Z.: Enhancing motion deblurring in high-speed scenes with spike streams. Adv. Neural Inf. Process. Syst. 36 (2024)"},{"key":"1_CR8","doi-asserted-by":"crossref","unstructured":"Cho, H., Jeong, Y., Kim, T., Yoon, K.J.: Non-coaxial event-guided motion deblurring with spatial alignment. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 12492\u201312503 (2023)","DOI":"10.1109\/ICCV51070.2023.01148"},{"issue":"1","key":"1_CR9","doi-asserted-by":"publisher","first-page":"154","DOI":"10.1109\/TPAMI.2020.3008413","volume":"44","author":"G Gallego","year":"2020","unstructured":"Gallego, G., et al.: Event-based vision: a survey. IEEE Trans. Pattern Anal. Mach. Intell. 44(1), 154\u2013180 (2020)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"1_CR10","doi-asserted-by":"crossref","unstructured":"Gehrig, D., Loquercio, A., Derpanis, K.G., Scaramuzza, D.: End-to-end learning of representations for asynchronous event-based data. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 5633\u20135643 (2019)","DOI":"10.1109\/ICCV.2019.00573"},{"key":"1_CR11","doi-asserted-by":"crossref","unstructured":"Hyun\u00a0Kim, T., Mu\u00a0Lee, K., Scholkopf, B., Hirsch, M.: Online video deblurring via dynamic temporal blending network. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 4038\u20134047 (2017)","DOI":"10.1109\/ICCV.2017.435"},{"key":"1_CR12","doi-asserted-by":"publisher","unstructured":"Jiang, B., Xie, Z., Xia, Z., Li, S., Liu, S.: ERDN: equivalent receptive field deformable network for video deblurring. In: Avidan, S., Brostow, G., Ciss\u00e9, M., Farinella, G.M., Hassner, T. (eds.) ECCV 2022. LNCS, vol. 13678, pp. 663\u2013678. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-19797-0_38","DOI":"10.1007\/978-3-031-19797-0_38"},{"key":"1_CR13","doi-asserted-by":"crossref","unstructured":"Jiang, Z., Zhang, Y., Zou, D., Ren, J., Lv, J., Liu, Y.: Learning event-based motion deblurring. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 3320\u20133329 (2020)","DOI":"10.1109\/CVPR42600.2020.00338"},{"key":"1_CR14","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"111","DOI":"10.1007\/978-3-030-01219-9_7","volume-title":"Computer Vision \u2013 ECCV 2018","author":"TH Kim","year":"2018","unstructured":"Kim, T.H., Sajjadi, M.S.M., Hirsch, M., Sch\u00f6lkopf, B.: Spatio-temporal transformer network for video restoration. In: Ferrari, V., Hebert, M., Sminchisescu, C., Weiss, Y. (eds.) ECCV 2018. LNCS, vol. 11207, pp. 111\u2013127. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-01219-9_7"},{"key":"1_CR15","doi-asserted-by":"publisher","unstructured":"Kim, T., Lee, J., Wang, L., Yoon, K.J.: Event-guided deblurring of unknown exposure time videos. In: European Conference on Computer Vision, pp. 519\u2013538. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-19797-0_30","DOI":"10.1007\/978-3-031-19797-0_30"},{"key":"1_CR16","doi-asserted-by":"crossref","unstructured":"Li, D., et al.: A simple baseline for video restoration with grouped spatial-temporal shift. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 9822\u20139832 (2023)","DOI":"10.1109\/CVPR52729.2023.00947"},{"key":"1_CR17","unstructured":"Liang, J., et al.: VRT: a video restoration transformer. arXiv preprint arXiv:2201.12288 (2022)"},{"key":"1_CR18","first-page":"378","volume":"35","author":"J Liang","year":"2022","unstructured":"Liang, J., et al.: Recurrent video restoration transformer with guided deformable attention. Adv. Neural. Inf. Process. Syst. 35, 378\u2013393 (2022)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"1_CR19","unstructured":"Lin, J., et al.: Flow-guided sparse transformer for video deblurring. arXiv preprint arXiv:2201.01893 (2022)"},{"key":"1_CR20","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"695","DOI":"10.1007\/978-3-030-58598-3_41","volume-title":"Computer Vision \u2013 ECCV 2020","author":"S Lin","year":"2020","unstructured":"Lin, S., et al.: Learning event-driven video deblurring and interpolation. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, J.-M. (eds.) ECCV 2020. LNCS, vol. 12353, pp. 695\u2013710. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-58598-3_41"},{"key":"1_CR21","doi-asserted-by":"crossref","unstructured":"Mildenhall, B., Barron, J.T., Chen, J., Sharlet, D., Ng, R., Carroll, R.: Burst denoising with kernel prediction networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 2502\u20132510 (2018)","DOI":"10.1109\/CVPR.2018.00265"},{"key":"1_CR22","doi-asserted-by":"crossref","unstructured":"Nah, S., et al.: Ntire 2019 challenge on video deblurring and super-resolution: dataset and study. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops (2019)","DOI":"10.1109\/CVPRW.2019.00251"},{"key":"1_CR23","doi-asserted-by":"crossref","unstructured":"Nah, S., Hyun\u00a0Kim, T., Mu\u00a0Lee, 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":"1_CR24","doi-asserted-by":"publisher","unstructured":"Oh, J., Kim, M.: DeMFI: deep joint deblurring and multi-frame interpolation with flow-guided attentive correlation and recursive boosting. In: Avidan, S., Brostow, G., Ciss\u00e9, M., Farinella, G.M., Hassner, T. (eds.) ECCV 2022. LNCS, vol. 13667, pp. 198\u2013215. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-20071-7_12","DOI":"10.1007\/978-3-031-20071-7_12"},{"key":"1_CR25","doi-asserted-by":"crossref","unstructured":"Pan, J., Bai, H., Tang, J.: Cascaded deep video deblurring using temporal sharpness prior. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 3043\u20133051 (2020)","DOI":"10.1109\/CVPR42600.2020.00311"},{"key":"1_CR26","doi-asserted-by":"crossref","unstructured":"Pan, J., Xu, B., Dong, J., Ge, J., Tang, J.: Deep discriminative spatial and temporal network for efficient video deblurring. In: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2023)","DOI":"10.1109\/CVPR52729.2023.02125"},{"key":"1_CR27","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":"1_CR28","doi-asserted-by":"crossref","unstructured":"Ranjan, A., Black, M.J.: Optical flow estimation using a spatial pyramid network. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 4161\u20134170 (2017)","DOI":"10.1109\/CVPR.2017.291"},{"key":"1_CR29","unstructured":"Rebecq, H., Gehrig, D., Scaramuzza, D.: ESIM: an open event camera simulator. In: Conference on Robot Learning, pp. 969\u2013982. PMLR (2018)"},{"key":"1_CR30","doi-asserted-by":"publisher","unstructured":"Rim, J., Kim, G., Kim, J., Lee, J., Lee, S., Cho, S.: Realistic blur synthesis for learning image deblurring. In: Avidan, S., Brostow, G., Ciss\u00e9, M., Farinella, G.M., Hassner, T. (eds.) ECCV 2022. LNCS, vol. 12370, pp. 184\u2013201. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-20071-7_29","DOI":"10.1007\/978-3-031-20071-7_29"},{"key":"1_CR31","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"184","DOI":"10.1007\/978-3-030-58595-2_12","volume-title":"Computer Vision \u2013 ECCV 2020","author":"J Rim","year":"2020","unstructured":"Rim, J., Lee, H., Won, J., Cho, S.: Real-world blur dataset for learning and benchmarking deblurring algorithms. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, J.-M. (eds.) ECCV 2020. LNCS, vol. 12370, pp. 184\u2013201. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-58595-2_12"},{"key":"1_CR32","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"234","DOI":"10.1007\/978-3-319-24574-4_28","volume-title":"Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2015","author":"O Ronneberger","year":"2015","unstructured":"Ronneberger, O., Fischer, P., Brox, T.: U-Net: convolutional networks for biomedical image segmentation. In: Navab, N., Hornegger, J., Wells, W.M., Frangi, A.F. (eds.) MICCAI 2015. LNCS, vol. 9351, pp. 234\u2013241. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-24574-4_28"},{"key":"1_CR33","doi-asserted-by":"crossref","unstructured":"Shang, W., Ren, D., Zou, D., Ren, J.S., Luo, P., Zuo, W.: Bringing events into video deblurring with non-consecutively blurry frames. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision (ICCV), pp. 4531\u20134540 (2021)","DOI":"10.1109\/ICCV48922.2021.00449"},{"key":"1_CR34","doi-asserted-by":"publisher","first-page":"277","DOI":"10.1109\/TIP.2020.3033617","volume":"30","author":"W Shen","year":"2020","unstructured":"Shen, W., Bao, W., Zhai, G., Chen, L., Min, X., Gao, Z.: Video frame interpolation and enhancement via pyramid recurrent framework. IEEE Trans. Image Process. 30, 277\u2013292 (2020)","journal-title":"IEEE Trans. Image Process."},{"key":"1_CR35","doi-asserted-by":"crossref","unstructured":"Su, S., Delbracio, M., Wang, J., Sapiro, G., Heidrich, W., Wang, O.: Deep video deblurring for hand-held cameras. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1279\u20131288 (2017)","DOI":"10.1109\/CVPR.2017.33"},{"key":"1_CR36","doi-asserted-by":"publisher","unstructured":"Sun, L., et al.: Event-based fusion for motion deblurring with cross-modal attention. In: Avidan, S., Brostow, G., Ciss\u00e9, M., Farinella, G.M., Hassner, T. (eds.) ECCV 2022. LNCS, vol. 13678, pp. 412\u2013428. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-19797-0_24","DOI":"10.1007\/978-3-031-19797-0_24"},{"key":"1_CR37","doi-asserted-by":"crossref","unstructured":"Sun, L., et al.: Event-based frame interpolation with ad-hoc deblurring. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 18043\u201318052 (2023)","DOI":"10.1109\/CVPR52729.2023.01730"},{"key":"1_CR38","unstructured":"Vaswani, A., et al.: Attention is all you need. In: NIPS, pp. 5998\u20136008 (2017)"},{"key":"1_CR39","doi-asserted-by":"crossref","unstructured":"Wang, X., Chan, K.C., Yu, K., Dong, C., Change\u00a0Loy, C.: EDVR: video restoration with enhanced deformable convolutional networks. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops (2019)","DOI":"10.1109\/CVPRW.2019.00247"},{"key":"1_CR40","doi-asserted-by":"publisher","unstructured":"Wang, Y., et al.: Efficient video deblurring guided by motion magnitude and convolutional block attention module. In: Wang, W., Mu, J., Liu, X., Na, Z.N. (eds.) AIC 2023. LNEE, vol. 1043, pp. 259\u2013267. Springer, Singapore (2024). https:\/\/doi.org\/10.1007\/978-981-99-7545-7_27","DOI":"10.1007\/978-981-99-7545-7_27"},{"key":"1_CR41","doi-asserted-by":"crossref","unstructured":"Wei, K., Fu, Y., Yang, J., Huang, H.: A physics-based noise formation model for extreme low-light raw denoising. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 2758\u20132767 (2020)","DOI":"10.1109\/CVPR42600.2020.00283"},{"key":"1_CR42","doi-asserted-by":"crossref","unstructured":"Wieschollek, P., Hirsch, M., Scholkopf, B., Lensch, H.: Learning blind motion deblurring. In: ICCV, pp. 231\u2013240 (2017)","DOI":"10.1109\/ICCV.2017.34"},{"key":"1_CR43","doi-asserted-by":"crossref","unstructured":"Xu, F., et al.: Motion deblurring with real events. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision (ICCV), pp. 2583\u20132592 (2021)","DOI":"10.1109\/ICCV48922.2021.00258"},{"key":"1_CR44","doi-asserted-by":"crossref","unstructured":"Zamir, S.W., Arora, A., Khan, S., Hayat, M., Khan, F.S., Yang, M.H.: Restormer: efficient transformer for high-resolution image restoration. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 5728\u20135739 (2022)","DOI":"10.1109\/CVPR52688.2022.00564"},{"key":"1_CR45","doi-asserted-by":"crossref","unstructured":"Zamir, S.W., et al.: Multi-stage progressive image restoration. arXiv preprint arXiv:2102.02808 (2021)","DOI":"10.1109\/CVPR46437.2021.01458"},{"key":"1_CR46","doi-asserted-by":"publisher","unstructured":"Zhang, H., Xie, H., Yao, H.: Spatio-temporal deformable attention network for video deblurring. In: Avidan, S., Brostow, G., Ciss\u00e9, M., Farinella, G.M., Hassner, T. (eds.) ECCV 2022. LNCS, vol. 13676, pp. 581\u2013596. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-19787-1_33","DOI":"10.1007\/978-3-031-19787-1_33"},{"key":"1_CR47","doi-asserted-by":"crossref","unstructured":"Zhang, K., Luo, W., Zhong, Y., Ma, L., Liu, W., Li, H.: Adversarial spatio-temporal learning for video deblurring. IEEE Trans. Image Process. (2018)","DOI":"10.1109\/TIP.2018.2867733"},{"key":"1_CR48","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"352","DOI":"10.1007\/978-3-030-67832-6_29","volume-title":"MultiMedia Modeling","author":"L Zhang","year":"2021","unstructured":"Zhang, L., Zhang, H., Zhu, C., Guo, S., Chen, J., Wang, L.: Fine-grained video deblurring with event camera. In: Loko\u010d, J., et al. (eds.) MMM 2021. LNCS, vol. 12572, pp. 352\u2013364. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-67832-6_29"},{"key":"1_CR49","doi-asserted-by":"crossref","unstructured":"Zhang, X., Yu, L.: Unifying motion deblurring and frame interpolation with events. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 17765\u201317774 (2022)","DOI":"10.1109\/CVPR52688.2022.01724"},{"key":"1_CR50","doi-asserted-by":"crossref","unstructured":"Zhang, X., Yu, L., Yang, W., Liu, J., Xia, G.S.: Generalizing event-based motion deblurring in real-world scenarios. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 10734\u201310744 (2023)","DOI":"10.1109\/ICCV51070.2023.00985"},{"key":"1_CR51","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Qin, H., Wang, X., Li, H.: Rethinking noise synthesis and modeling in raw denoising. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 4593\u20134601 (2021)","DOI":"10.1109\/ICCV48922.2021.00455"},{"key":"1_CR52","doi-asserted-by":"crossref","unstructured":"Zhong, Z., Cao, M., Ji, X., Zheng, Y., Sato, I.: Blur interpolation transformer for real-world motion from blur. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 5713\u20135723 (2023)","DOI":"10.1109\/CVPR52729.2023.00553"},{"key":"1_CR53","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":"1_CR54","doi-asserted-by":"crossref","unstructured":"Zhong, Z., Zheng, Y., Sato, I.: Towards rolling shutter correction and deblurring in dynamic scenes. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 9219\u20139228 (2021)","DOI":"10.1109\/CVPR46437.2021.00910"},{"key":"1_CR55","doi-asserted-by":"crossref","unstructured":"Zhou, J., Jampani, V., Pi, Z., Liu, Q., Yang, M.H.: Decoupled dynamic filter networks. In: IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2021)","DOI":"10.1109\/CVPR46437.2021.00658"},{"key":"1_CR56","doi-asserted-by":"crossref","unstructured":"Zhu, A.Z., Yuan, L., Chaney, K., Daniilidis, K.: Unsupervised event-based learning of optical flow, depth, and egomotion. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 989\u2013997 (2019)","DOI":"10.1109\/CVPR.2019.00108"},{"key":"1_CR57","doi-asserted-by":"crossref","unstructured":"Zhu, C., et al.: Deep recurrent neural network with multi-scale bi-directional propagation for video deblurring. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol.\u00a036, pp. 3598\u20133607 (2022)","DOI":"10.1609\/aaai.v36i3.20272"},{"key":"1_CR58","doi-asserted-by":"crossref","unstructured":"Zhu, X., Hu, H., Lin, S., Dai, J.: Deformable convnets v2: more deformable, better results. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 9308\u20139316 (2019)","DOI":"10.1109\/CVPR.2019.00953"}],"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\/978-3-031-72943-0_1","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,28]],"date-time":"2024-11-28T14:14:31Z","timestamp":1732803271000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-72943-0_1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,29]]},"ISBN":["9783031729423","9783031729430"],"references-count":58,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-72943-0_1","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,11,29]]},"assertion":[{"value":"29 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"}}]}}