{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T14:36:16Z","timestamp":1742913376899,"version":"3.40.3"},"publisher-location":"Cham","reference-count":45,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030585822"},{"type":"electronic","value":"9783030585839"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"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":[[2020]]},"DOI":"10.1007\/978-3-030-58583-9_19","type":"book-chapter","created":{"date-parts":[[2020,11,18]],"date-time":"2020-11-18T10:08:18Z","timestamp":1605694098000},"page":"309-325","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["FreeCam3D: Snapshot Structured Light 3D with Freely-Moving Cameras"],"prefix":"10.1007","author":[{"given":"Yicheng","family":"Wu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Vivek","family":"Boominathan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xuan","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jacob T.","family":"Robinson","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hiroshi","family":"Kawasaki","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Aswin","family":"Sankaranarayanan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ashok","family":"Veeraraghavan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,11,19]]},"reference":[{"key":"19_CR1","doi-asserted-by":"crossref","unstructured":"Benveniste, R., \u00dcnsalan, C.: A color invariant based binary coded structured light range scanner for shiny objects. In: International Conference on Pattern Recognition (ICPR), pp. 798\u2013801 (2010)","DOI":"10.1109\/ICPR.2010.201"},{"key":"19_CR2","volume-title":"Learning OpenCV: Computer Vision with the OpenCV Library","author":"G Bradski","year":"2008","unstructured":"Bradski, G., Kaehler, A.: Learning OpenCV: Computer Vision with the OpenCV Library. O\u2019Reilly Media Inc., Sebastopol (2008)"},{"key":"19_CR3","unstructured":"Chakrabarti, A.: Learning sensor multiplexing design through back-propagation. In: Advances in Neural Information Processing Systems (NeurIPS), pp. 3081\u20133089 (2016)"},{"key":"19_CR4","doi-asserted-by":"crossref","unstructured":"Chang, J., Wetzstein, G.: Deep optics for monocular depth estimation and 3D object detection. In: IEEE International Conference on Computer Vision (ICCV), pp. 10193\u201310202 (2019)","DOI":"10.1109\/ICCV.2019.01029"},{"issue":"7","key":"19_CR5","doi-asserted-by":"publisher","first-page":"1777","DOI":"10.1364\/JOSAA.15.001777","volume":"15","author":"H Farid","year":"1998","unstructured":"Farid, H., Simoncelli, E.P.: Range estimation by optical differentiation. J. Opt. Soc. Am. A (JOSA A) 15(7), 1777\u20131786 (1998)","journal-title":"J. Opt. Soc. Am. A (JOSA A)"},{"key":"19_CR6","doi-asserted-by":"crossref","unstructured":"Furukawa, R., Nagamatsu, G., Kawasaki, H.: Simultaneous shape registration and active stereo shape reconstruction using modified bundle adjustment. In: International Conference on 3D Vision (3DV), pp. 453\u2013462 (2019)","DOI":"10.1109\/3DV.2019.00057"},{"key":"19_CR7","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"16","DOI":"10.1007\/978-3-319-67543-5_2","volume-title":"Computer Assisted and Robotic Endoscopy and Clinical Image-Based Procedures","author":"R Furukawa","year":"2017","unstructured":"Furukawa, R., et al.: 3D endoscope system using asynchronously blinking grid pattern projection for HDR image synthesis. In: Cardoso, M.J., et al. (eds.) CARE\/CLIP -2017. LNCS, vol. 10550, pp. 16\u201328. Springer, Cham (2017). https:\/\/doi.org\/10.1007\/978-3-319-67543-5_2"},{"issue":"8","key":"19_CR8","doi-asserted-by":"publisher","first-page":"930","DOI":"10.1109\/TPAMI.2003.1217599","volume":"25","author":"XS Gao","year":"2003","unstructured":"Gao, X.S., Hou, X.R., Tang, J., Cheng, H.F.: Complete solution classification for the perspective-three-point problem. IEEE Trans. Pattern Anal. Mach. Intell. (TPAMI) 25(8), 930\u2013943 (2003)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell. (TPAMI)"},{"key":"19_CR9","doi-asserted-by":"crossref","unstructured":"Girod, B., Scherock, S.: Depth from defocus of structured light. In: Optics, Illumination, and Image Sensing for Machine Vision IV, vol. 1194, pp. 209\u2013215 (1990)","DOI":"10.1117\/12.969853"},{"key":"19_CR10","doi-asserted-by":"crossref","unstructured":"Godard, C., Mac Aodha, O., Brostow, G.J.: Unsupervised monocular depth estimation with left-right consistency. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 270\u2013279 (2017)","DOI":"10.1109\/CVPR.2017.699"},{"key":"19_CR11","volume-title":"Introduction to Fourier optics","author":"JW Goodman","year":"2005","unstructured":"Goodman, J.W.: Introduction to Fourier optics. Roberts and Company Publishers, Greenwood Village (2005)"},{"key":"19_CR12","doi-asserted-by":"crossref","unstructured":"Guo, Q., Alexander, E., Zickler, T.: Focal track: depth and accommodation with oscillating lens deformation. In: IEEE International Conference on Computer Vision (ICCV), pp. 966\u2013974 (2017)","DOI":"10.1109\/ICCV.2017.110"},{"issue":"3","key":"19_CR13","doi-asserted-by":"publisher","first-page":"298","DOI":"10.1109\/TCI.2018.2849326","volume":"4","author":"H Haim","year":"2018","unstructured":"Haim, H., Elmalem, S., Giryes, R., Bronstein, A.M., Marom, E.: Depth estimation from a single image using deep learned phase coded mask. IEEE Trans. Comput. Imaging (TCI) 4(3), 298\u2013310 (2018)","journal-title":"IEEE Trans. Comput. Imaging (TCI)"},{"key":"19_CR14","doi-asserted-by":"publisher","first-page":"88","DOI":"10.2197\/ipsjtcva.6.88","volume":"6","author":"M Hitoshi","year":"2014","unstructured":"Hitoshi, M., Hiroshi, K., Ryo, F.: Depth from projector\u2019s defocus based on multiple focus pattern projection. IPSJ Trans. Comput. Vis. Appl. (CVA) 6, 88\u201392 (2014)","journal-title":"IPSJ Trans. Comput. Vis. Appl. (CVA)"},{"key":"19_CR15","unstructured":"Jaderberg, M., Simonyan, K., Zisserman, A., et al.: Spatial transformer networks. In: Advances in Neural Information Processing Systems (NeurIPS), pp. 2017\u20132025 (2015)"},{"key":"19_CR16","doi-asserted-by":"crossref","unstructured":"Kawasaki, H., Furukawa, R., Sagawa, R., Yagi, Y.: Dynamic scene shape reconstruction using a single structured light pattern. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1\u20138. IEEE (2008)","DOI":"10.1109\/CVPR.2008.4587702"},{"key":"19_CR17","doi-asserted-by":"crossref","unstructured":"Kawasaki, H., Horita, Y., Masuyama, H., Ono, S., Kimura, M., Takane, Y.: Optimized aperture for estimating depth from projector\u2019s defocus. In: International Conference on 3D Vision (3DV), pp. 135\u2013142 (2013)","DOI":"10.1109\/3DV.2013.26"},{"key":"19_CR18","doi-asserted-by":"crossref","unstructured":"Kawasaki, H., et al.: Structured light with coded aperture for wide range 3D measurement. In: IEEE Conference on Image Processing (ICIP), pp. 2777\u20132780 (2012)","DOI":"10.1109\/ICIP.2012.6467475"},{"key":"19_CR19","doi-asserted-by":"crossref","unstructured":"Lee, J., Gupta, M.: Stochastic exposure coding for handling multi-ToF-camera interference. In: IEEE International Conference on Computer Vision (ICCV), pp. 7880\u20137888 (2019)","DOI":"10.1109\/ICCV.2019.00797"},{"key":"19_CR20","doi-asserted-by":"crossref","unstructured":"Lei, Y., Bengtson, K.R., Li, L., Allebach, J.P.: Design and decoding of an m-array pattern for low-cost structured light 3D reconstruction systems. In: IEEE International Conference on Image Processing (ICIP), pp. 2168\u20132172 (2013)","DOI":"10.1109\/ICIP.2013.6738447"},{"issue":"2","key":"19_CR21","doi-asserted-by":"publisher","first-page":"155","DOI":"10.1007\/s11263-008-0152-6","volume":"81","author":"V Lepetit","year":"2009","unstructured":"Lepetit, V., Moreno-Noguer, F., Fua, P.: EPnP: An accurate o($$n$$) solution to the P$$n$$P problem. Int. J. Comput. Vis. (IJCV) 81(2), 155 (2009). https:\/\/doi.org\/10.1007\/s11263-008-0152-6","journal-title":"Int. J. Comput. Vis. (IJCV)"},{"issue":"3","key":"19_CR22","doi-asserted-by":"publisher","first-page":"70","DOI":"10.1145\/1276377.1276464","volume":"26","author":"A Levin","year":"2007","unstructured":"Levin, A., Fergus, R., Durand, F., Freeman, W.T.: Image and depth from a conventional camera with a coded aperture. ACM Trans. Graph. (TOG) 26(3), 70 (2007)","journal-title":"ACM Trans. Graph. (TOG)"},{"key":"19_CR23","doi-asserted-by":"crossref","unstructured":"Li, Q., Biswas, M., Pickering, M.R., Frater, M.R.: Accurate depth estimation using structured light and passive stereo disparity estimation. In: IEEE International Conference on Image Processing (ICIP), pp. 969\u2013972 (2011)","DOI":"10.1109\/ICIP.2011.6116723"},{"key":"19_CR24","unstructured":"Li, W., et al.: InteriorNet: mega-scale multi-sensor photo-realistic indoor scenes dataset. arXiv:1809.00716 (2018)"},{"key":"19_CR25","doi-asserted-by":"crossref","unstructured":"Mayer, N., et al.: A large dataset to train convolutional networks for disparity, optical flow, and scene flow estimation. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 4040\u20134048 (2016)","DOI":"10.1109\/CVPR.2016.438"},{"key":"19_CR26","unstructured":"McCormac, J., Handa, A., Leutenegger, S., Davison, A.J.: SceneNet RGB-D: 5M photorealistic images of synthetic indoor trajectories with ground truth. arXiv:1612.05079 (2016)"},{"key":"19_CR27","doi-asserted-by":"crossref","unstructured":"Metzler, C.A., Ikoma, H., Peng, Y., Wetzstein, G.: Deep optics for single-shot high-dynamic-range imaging. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1375\u20131385 (2020)","DOI":"10.1109\/CVPR42600.2020.00145"},{"key":"19_CR28","unstructured":"Microsoft: Xbox 360 Kinect (2010). http:\/\/www.xbox.com\/en-US\/kinect"},{"key":"19_CR29","unstructured":"Microsoft: Kinect for Windows (2013). http:\/\/www.microsoft.com\/en-us\/"},{"issue":"12","key":"19_CR30","doi-asserted-by":"publisher","first-page":"1186","DOI":"10.1109\/34.546256","volume":"18","author":"S Nayar","year":"1996","unstructured":"Nayar, S., Watanabe, M., Noguchi, M.: Real-time focus range sensor. IEEE Trans. Pattern Anal. Mach. Intell. (TPAMI) 18(12), 1186\u20131198 (1996)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell. (TPAMI)"},{"issue":"9","key":"19_CR31","doi-asserted-by":"publisher","first-page":"2995","DOI":"10.1073\/pnas.0900245106","volume":"106","author":"SRP Pavani","year":"2009","unstructured":"Pavani, S.R.P., et al.: Three-dimensional, single-molecule fluorescence imaging beyond the diffraction limit by using a double-helix point spread function. Proc. Natl. Acad. Sci. (PNAS) 106(9), 2995\u20132999 (2009)","journal-title":"Proc. Natl. Acad. Sci. (PNAS)"},{"key":"19_CR32","doi-asserted-by":"crossref","unstructured":"Riegler, G., Liao, Y., Donne, S., Koltun, V., Geiger, A.: Connecting the dots: learning representations for active monocular depth estimation. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 7624\u20137633 (2019)","DOI":"10.1109\/CVPR.2019.00781"},{"key":"19_CR33","doi-asserted-by":"crossref","unstructured":"Ronneberger, O., Fischer, P., Brox, T.: U-Net: convolutional networks for biomedical image segmentation. In: International Conference on Medical image computing and computer-assisted intervention (MICCAI), pp. 234\u2013241 (2015)","DOI":"10.1007\/978-3-319-24574-4_28"},{"issue":"8","key":"19_CR34","doi-asserted-by":"publisher","first-page":"2666","DOI":"10.1016\/j.patcog.2010.03.004","volume":"43","author":"J Salvi","year":"2010","unstructured":"Salvi, J., Fernandez, S., Pribanic, T., Llado, X.: A state of the art in structured light patterns for surface profilometry. Pattern Recogn. 43(8), 2666\u20132680 (2010)","journal-title":"Pattern Recogn."},{"issue":"13","key":"19_CR35","doi-asserted-by":"publisher","first-page":"133902","DOI":"10.1103\/PhysRevLett.113.133902","volume":"113","author":"Y Shechtman","year":"2014","unstructured":"Shechtman, Y., Sahl, S.J., Backer, A.S., Moerner, W.: Optimal point spread function design for 3D imaging. Phys. Rev. Lett. (PRL) 113(13), 133902 (2014)","journal-title":"Phys. Rev. Lett. (PRL)"},{"issue":"4","key":"19_CR36","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3197517.3201333","volume":"37","author":"V Sitzmann","year":"2018","unstructured":"Sitzmann, V., et al.: End-to-end optimization of optics and image processing for achromatic extended depth of field and super-resolution imaging. ACM Trans. Graph. (TOG) 37(4), 1\u201313 (2018)","journal-title":"ACM Trans. Graph. (TOG)"},{"key":"19_CR37","doi-asserted-by":"crossref","unstructured":"Sun, Q., Tseng, E., Fu, Q., Heidrich, W., Heide, F.: Learning rank-1 diffractive optics for single-shot high dynamic range imaging. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1386\u20131396 (2020)","DOI":"10.1109\/CVPR42600.2020.00146"},{"issue":"10","key":"19_CR38","doi-asserted-by":"publisher","first-page":"104104","DOI":"10.1117\/1.OE.53.10.104104","volume":"53","author":"S Tang","year":"2014","unstructured":"Tang, S., Zhang, X., Tu, D.: Fuzzy decoding in color-coded structured light. Opt. Eng. 53(10), 104104 (2014)","journal-title":"Opt. Eng."},{"issue":"1","key":"19_CR39","doi-asserted-by":"publisher","first-page":"138","DOI":"10.1006\/cviu.1999.0832","volume":"78","author":"PH Torr","year":"2000","unstructured":"Torr, P.H., Zisserman, A.: MLESAC: a new robust estimator with application to estimating image geometry. Comput. Vis. Image Underst. (CVIU) 78(1), 138\u2013156 (2000)","journal-title":"Comput. Vis. Image Underst. (CVIU)"},{"key":"19_CR40","doi-asserted-by":"crossref","unstructured":"Ulusoy, A.O., Calakli, F., Taubin, G.: Robust one-shot 3D scanning using loopy belief propagation. In: IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 15\u201322 (2010)","DOI":"10.1109\/CVPRW.2010.5543556"},{"issue":"3","key":"19_CR41","doi-asserted-by":"publisher","first-page":"69","DOI":"10.1145\/1276377.1276463","volume":"26","author":"A Veeraraghavan","year":"2007","unstructured":"Veeraraghavan, A., Raskar, R., Agrawal, A., Mohan, A., Tumblin, J.: Dappled photography: mask enhanced cameras for heterodyned light fields and coded aperture refocusing. ACM Trans. Graph. (TOG) 26(3), 69 (2007)","journal-title":"ACM Trans. Graph. (TOG)"},{"issue":"3","key":"19_CR42","doi-asserted-by":"publisher","first-page":"203","DOI":"10.1023\/A:1007905828438","volume":"27","author":"M Watanabe","year":"1998","unstructured":"Watanabe, M., Nayar, S.K.: Rational filters for passive depth from defocus. Int. J. Comput. Vis. (IJCV) 27(3), 203\u2013225 (1998). https:\/\/doi.org\/10.1023\/A:1007905828438","journal-title":"Int. J. Comput. Vis. (IJCV)"},{"key":"19_CR43","doi-asserted-by":"crossref","unstructured":"Wu, Y., Boominathan, V., Chen, H., Sankaranarayanan, A., Veeraraghavan, A.: PhaseCam3D-learning phase masks for passive single view depth estimation. In: IEEE International Conference on Computational Photography (ICCP), pp. 1\u201312 (2019)","DOI":"10.1109\/ICCPHOT.2019.8747330"},{"issue":"22","key":"19_CR44","doi-asserted-by":"publisher","first-page":"5340","DOI":"10.1364\/AO.51.005340","volume":"51","author":"X Zhang","year":"2012","unstructured":"Zhang, X., Li, Y., Zhu, L.: Color code identification in coded structured light. Appl. Opt. 51(22), 5340\u20135356 (2012)","journal-title":"Appl. Opt."},{"key":"19_CR45","doi-asserted-by":"crossref","unstructured":"Zhou, T., Brown, M., Snavely, N., Lowe, D.G.: Unsupervised learning of depth and ego-motion from video. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1851\u20131858 (2017)","DOI":"10.1109\/CVPR.2017.700"}],"container-title":["Lecture Notes in Computer Science","Computer Vision \u2013 ECCV 2020"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-58583-9_19","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,18]],"date-time":"2024-11-18T00:08:14Z","timestamp":1731888494000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-58583-9_19"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030585822","9783030585839"],"references-count":45,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-58583-9_19","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"19 November 2020","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":"Glasgow","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"United Kingdom","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23 August 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28 August 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"eccv2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/eccv2020.eu\/","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":"OpenReview","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"5025","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":"1360","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":"27% - 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":"7","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)"}},{"value":"The conference was held virtually due to the COVID-19 pandemic. From the ECCV Workshops 249 full papers, 18 short papers, and 21 further contributions were published out of a total of 467 submissions.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}