{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,17]],"date-time":"2026-08-17T15:00:19Z","timestamp":1786978819695,"version":"build-2736575974"},"publisher-location":"Cham","reference-count":45,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030668228","type":"print"},{"value":"9783030668235","type":"electronic"}],"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:\/\/2.zoppoz.workers.dev:443\/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:\/\/2.zoppoz.workers.dev:443\/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\/978-3-030-66823-5_29","type":"book-chapter","created":{"date-parts":[[2021,1,2]],"date-time":"2021-01-02T02:03:14Z","timestamp":1609552994000},"page":"485-499","update-policy":"https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Motion Prediction for First-Person Vision Multi-object Tracking"],"prefix":"10.1007","author":[{"given":"Ricardo","family":"Sanchez-Matilla","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrea","family":"Cavallaro","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2021,1,3]]},"reference":[{"key":"29_CR1","unstructured":"MOT17: A benchmark for multi-object tracking (2016). https:\/\/2.zoppoz.workers.dev:443\/https\/motchallenge.net\/data\/MOT17\/. Accessed 15 July 2020"},{"key":"29_CR2","doi-asserted-by":"crossref","unstructured":"Alahi, A., Goel, K., Ramanathan, V., Robicquet, A., Fei-Fei, L., Savarese, S.: Social LSTM: human trajectory prediction in crowded spaces. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Las Vegas, NV, pp. 961\u2013971, June 2016","DOI":"10.1109\/CVPR.2016.110"},{"issue":"2","key":"29_CR3","doi-asserted-by":"publisher","first-page":"149","DOI":"10.1049\/iet-its.2009.0073","volume":"4","author":"J Arrospide","year":"2010","unstructured":"Arrospide, J., Salgado, L., Nieto, M., Mohedano, R.: Homography-based ground plane detection using a single on-board camera. IET Intell. Transp. Syst. 4(2), 149\u2013160 (2010)","journal-title":"IET Intell. Transp. Syst."},{"key":"29_CR4","doi-asserted-by":"crossref","unstructured":"Babaee, M., Li, Z., Rigoll, G.: Occlusion handling in tracking multiple people using RNN. In: Proceedings of the IEEE International Conference on Image Processing, Athens, Greece, pp. 2715\u20132719, October 2018","DOI":"10.1109\/ICIP.2018.8451140"},{"key":"29_CR5","unstructured":"Becker, S., Hug, R., H\u00fcbner, W., Arens, M.: An evaluation of trajectory prediction approaches and notes on the trajnet benchmark. arXiv:1805.07663 (2018)"},{"issue":"1","key":"29_CR6","doi-asserted-by":"publisher","first-page":"246","DOI":"10.1155\/2008\/246309","volume":"2008","author":"K Bernardin","year":"2008","unstructured":"Bernardin, K., Stiefelhagen, R.: Evaluating multiple object tracking performance: The CLEAR MOT Metrics. J. Image Video Proc. 2008(1), 246\u2013309 (2008). https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1155\/2008\/246309","journal-title":"J. Image Video Proc."},{"issue":"9","key":"29_CR7","doi-asserted-by":"publisher","first-page":"1820","DOI":"10.1109\/TPAMI.2010.232","volume":"33","author":"MD Breitenstein","year":"2011","unstructured":"Breitenstein, M.D., Reichlin, F., Leibe, B., Koller-Meier, E., Gool, L.V.: Online multiperson tracking-by-detection from a single, uncalibrated camera. IEEE Trans. Pattern Anal. Mach. Intell. 33(9), 1820\u20131833 (2011)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"29_CR8","doi-asserted-by":"crossref","unstructured":"Chandra, R., Bhattacharya, U., Bera, A., Manocha, D.: Traphic: trajectory prediction in dense and heterogeneous traffic using weighted interactions. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 8483\u20138492 (2019)","DOI":"10.1109\/CVPR.2019.00868"},{"key":"29_CR9","doi-asserted-by":"crossref","unstructured":"Chandra, R., Bhattacharya, U., Roncal, C., Bera, A., Manocha, D.: RobustTP: end-to-end trajectory prediction for heterogeneous road-agents in dense traffic with noisy sensor inputs. In: ACM Computer Science in Cars Symposium, pp. 1\u20139 (2019)","DOI":"10.1145\/3359999.3360495"},{"issue":"7","key":"29_CR10","doi-asserted-by":"publisher","first-page":"1577","DOI":"10.1109\/TPAMI.2012.248","volume":"35","author":"W Choi","year":"2013","unstructured":"Choi, W., Pantofaru, C., Savarese, S.: A general framework for tracking multiple people from a moving camera. IEEE Trans. Pattern Anal. Mach. Intell. 35(7), 1577\u20131591 (2013)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"29_CR11","doi-asserted-by":"crossref","unstructured":"Eiselein, V., Arp, D., P\u00e4tzold, M., Sikora, T.: Real-time multi-human tracking using a probability hypothesis density filter and multiple detectors. In: Proceedings of the IEEE Conference on Advanced Video and Signal Based Surveillance, Beijing, China, pp. 325\u2013330, September 2012","DOI":"10.1109\/AVSS.2012.59"},{"issue":"9","key":"29_CR12","doi-asserted-by":"publisher","first-page":"1627","DOI":"10.1109\/TPAMI.2009.167","volume":"32","author":"PF Felzenszwalb","year":"2010","unstructured":"Felzenszwalb, P.F., Girshick, R., Ramanan, D.: Object detection with discriminatively trained part based models. IEEE Trans. Pattern Anal. Mach. Intell. 32(9), 1627\u20131645 (2010)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"29_CR13","doi-asserted-by":"publisher","first-page":"14764","DOI":"10.1109\/ACCESS.2018.2816805","volume":"6","author":"Z Fu","year":"2018","unstructured":"Fu, Z., Feng, P., Angelini, F., Chambers, J., Naqvi, S.M.: Particle PHD filter based multiple human tracking using online group-structured dictionary learning. IEEE Access 6, 14764\u201314778 (2018). https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1109\/ACCESS.2018.2816805","journal-title":"IEEE Access"},{"key":"29_CR14","doi-asserted-by":"crossref","unstructured":"Gupta, A., Johnson, J., Fei-Fei, L., Savarese, S., Alahi, A.: Social GAN: socially acceptable trajectories with generative adversarial networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, June 2018","DOI":"10.1109\/CVPR.2018.00240"},{"key":"29_CR15","doi-asserted-by":"crossref","unstructured":"H. K. Galoogahi, F.H., Fagg, A., Huang, C., Ramanan, D., Lucey, S.: Need for speed: a benchmark for higher frame rate object tracking. In: Proceedings of the IEEE International Conference on Computer Vision, Honolulu, HI, pp. 1125\u20131134, October 2017","DOI":"10.1109\/ICCV.2017.128"},{"key":"29_CR16","doi-asserted-by":"publisher","first-page":"35","DOI":"10.1115\/1.3662552","volume":"82","author":"R Kalman","year":"1960","unstructured":"Kalman, R.: A new approach to linear filtering and prediction problems. Trans. ASME, J. Basic Eng. 82, 35\u201345 (1960)","journal-title":"Trans. ASME, J. Basic Eng."},{"key":"29_CR17","doi-asserted-by":"crossref","unstructured":"Kutbi, M., Chang, Y., Sun, B., Mordohai, P.: Learning to navigate robotic wheelchairs from demonstration: is training in simulation viable? In: Proceedings of the IEEE International Conference on Computer Vision Workshops, October 2019","DOI":"10.1109\/ICCVW.2019.00309"},{"key":"29_CR18","doi-asserted-by":"crossref","unstructured":"Kutschbach, T., Bochinski, E., Eiselein, V., Sikora, T.: Sequential sensor fusion combining probability hypothesis density and kernelized correlation filters for multi-object tracking in video data. In: Proceedings of the IEEE International Conference on Advanced Video and Signal Based Surveillance, Lecce, Italy, pp. 1\u20135, August 2017","DOI":"10.1109\/AVSS.2017.8078517"},{"key":"29_CR19","doi-asserted-by":"crossref","unstructured":"Lankton, S., Tannenbaum, A.: Improved tracking by decoupling camera and target motion. In: Proceedings SPIE, San Jose, CA, pp. 6811\u20136819 (2008)","DOI":"10.1117\/12.768453"},{"key":"29_CR20","doi-asserted-by":"publisher","first-page":"8181","DOI":"10.1109\/ACCESS.2018.2889442","volume":"7","author":"S Lee","year":"2019","unstructured":"Lee, S., Kim, E.: Multiple object tracking via feature pyramid siamese networks. IEEE Access 7, 8181\u20138194 (2019)","journal-title":"IEEE Access"},{"key":"29_CR21","doi-asserted-by":"publisher","first-page":"67316","DOI":"10.1109\/ACCESS.2018.2879535","volume":"6","author":"S Lee","year":"2018","unstructured":"Lee, S., Kim, M., Bae, S.: Learning discriminative appearance models for online multi-object tracking with appearance discriminability measures. IEEE Access 6, 67316\u201367328 (2018)","journal-title":"IEEE Access"},{"key":"29_CR22","doi-asserted-by":"crossref","unstructured":"Li, S., Yeung, D.: Visual object tracking for unmanned aerial vehicles: a benchmark and new motion models. In: Proceedings of the Association for the Advancement of Artificial Intelligence, San Francisco, CA, pp. 4140\u20134146, June 2017","DOI":"10.1609\/aaai.v31i1.11205"},{"key":"29_CR23","doi-asserted-by":"crossref","unstructured":"Lin, Y., Wang, K., Yi, W., Lian, S.: Deep learning based wearable assistive system for visually impaired people. In: Proceedings of the IEEE International Conference on Computer Vision Workshops, October 2019","DOI":"10.1109\/ICCVW.2019.00312"},{"key":"29_CR24","doi-asserted-by":"crossref","unstructured":"Lisotto, M., Coscia, P., Ballan, L.: Social and scene-aware trajectory prediction in crowded spaces. In: Proceedings of the IEEE International Conference on Computer Vision Workshops, October 2019","DOI":"10.1109\/ICCVW.2019.00314"},{"key":"29_CR25","unstructured":"Long, C., Haizhou, A., Zijie, Z., Chong, S.: Real-time multiple people tracking with deeply learned candidate selection and person re-identification. In: Proceedings of the IEEE International Conference on Multimedia and Expo, San Diego, CA (2018)"},{"issue":"8","key":"29_CR26","doi-asserted-by":"publisher","first-page":"1016","DOI":"10.1109\/TCSVT.2008.928221","volume":"18","author":"E Maggio","year":"2008","unstructured":"Maggio, E., Taj, M., Cavallaro, A.: Efficient multitarget visual tracking using random finite sets. IEEE Trans. Circuits Syst. Video Technol. 18(8), 1016\u20131027 (2008)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"29_CR27","unstructured":"Mahler, R.: A theoretical foundation for the Stein-Winter Probability Hypothesis Density (PHD) multitarget tracking approach. In: Proceedings of MSS National Symposium on Sensor and Data Fusion, San Diego, CA, USA, June 2002"},{"key":"29_CR28","unstructured":"M\u00e1ttyus, G., Benedek, C., Szir\u00e1nyi, T.: Multi target tracking on aerial videos. In: Proceedings of the ISPRS Workshop, Istanbul, Turkey (2010)"},{"key":"29_CR29","volume-title":"Generalized Linear Models","author":"P McCullagh","year":"2018","unstructured":"McCullagh, P.: Generalized Linear Models. Routledge, Boca Raton (2018)"},{"key":"29_CR30","doi-asserted-by":"crossref","unstructured":"Montemerlo, M., Thrun, S., Whittaker, W.: Conditional particle filters for simultaneous mobile robot localization and people-tracking. In: Proceedings of the IEEE International Conference on Robotics and Automation, pp. 695\u2013701 (2002)","DOI":"10.1109\/ROBOT.2002.1013439"},{"key":"29_CR31","doi-asserted-by":"crossref","unstructured":"Pfeiffer, M., Paolo, G., Sommer, H., Nieto, J., Siegwart, R., Cadena, C.: A data-driven model for interaction-aware pedestrian motion prediction in object cluttered environments. In: Proceedings of the IEEE International Conference on Robotics and Automation, Brisbane, Australia, pp. 1\u20138, May 2018","DOI":"10.1109\/ICRA.2018.8461157"},{"issue":"6","key":"29_CR32","doi-asserted-by":"publisher","first-page":"1137","DOI":"10.1109\/TPAMI.2016.2577031","volume":"39","author":"S Ren","year":"2017","unstructured":"Ren, S., He, K., Girshick, R., Sun, J.: Faster R-CNN: towards real-time object detection with region proposal networks. IEEE Trans. Pattern Anal. Mach. Intell. 39(6), 1137\u20131149 (2017)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"29_CR33","doi-asserted-by":"crossref","unstructured":"Sanchez-Matilla, R., Cavallaro, A.: Confidence intervals for tracking performance scores. In: Proceedings of the IEEE International Conference on Image Processing, Athens, Greece, pp. 246\u2013250, October 2018","DOI":"10.1109\/ICIP.2018.8451433"},{"key":"29_CR34","doi-asserted-by":"crossref","unstructured":"Sanchez-Matilla, R., Cavallaro, A.: A predictor of moving objects for first-person vision. In: Proceedings of the IEEE International Conference on Image Processing, Taipei, Taiwan, pp. 246\u2013250, September 2019","DOI":"10.1109\/ICIP.2019.8803140"},{"issue":"2","key":"29_CR35","doi-asserted-by":"publisher","first-page":"1642","DOI":"10.1109\/LRA.2020.2969200","volume":"5","author":"R Sanchez-Matilla","year":"2020","unstructured":"Sanchez-Matilla, R., et al.: Benchmark for human-to-robot handovers of unseen containers with unknown filling. IEEE Robot. Autom. Lett. 5(2), 1642\u20131649 (2020)","journal-title":"IEEE Robot. Autom. Lett."},{"key":"29_CR36","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"84","DOI":"10.1007\/978-3-319-48881-3_7","volume-title":"Computer Vision \u2013 ECCV 2016 Workshops","author":"R Sanchez-Matilla","year":"2016","unstructured":"Sanchez-Matilla, R., Poiesi, F., Cavallaro, A.: Online multi-target tracking with strong and weak detections. In: Hua, G., J\u00e9gou, H. (eds.) ECCV 2016. LNCS, vol. 9914, pp. 84\u201399. Springer, Cham (2016). https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1007\/978-3-319-48881-3_7"},{"key":"29_CR37","doi-asserted-by":"crossref","unstructured":"Shafique, K., Lee, M.W., Haering, N.: A rank constrained continuous formulation of multi-frame multi-target tracking problem. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Anchorage, AK, USA, pp. 1\u20138 (2008)","DOI":"10.1109\/CVPR.2008.4587577"},{"issue":"1","key":"29_CR38","first-page":"1","volume":"2","author":"R Szeliski","year":"2006","unstructured":"Szeliski, R.: Image alignment and stitching: a tutorial. Trans. Found. Trends Comp. Graph. Vis. 2(1), 1\u2013104 (2006)","journal-title":"Trans. Found. Trends Comp. Graph. Vis."},{"key":"29_CR39","doi-asserted-by":"crossref","unstructured":"Tapu, R., Mocanu, B., Zaharia, T.: Dynamic subtitles: a multimodal video accessibility enhancement dedicated to deaf and hearing impaired users. In: Proceedings of the IEEE International Conference on Computer Vision Workshops, October 2019","DOI":"10.1109\/ICCVW.2019.00313"},{"issue":"3","key":"29_CR40","doi-asserted-by":"publisher","first-page":"219","DOI":"10.1007\/s11263-015-0846-5","volume":"119","author":"H Wang","year":"2016","unstructured":"Wang, H., Oneata, D., Verbeek, J., Schmid, C.: A robust and efficient video representation for action recognition. Int. J. Comput. Vis. 119(3), 219\u2013238 (2016). https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1007\/s11263-015-0846-5","journal-title":"Int. J. Comput. Vis."},{"key":"29_CR41","series-title":"NATO ASI Series (Series D: Behavioural and Social Sciences)","doi-asserted-by":"publisher","first-page":"599","DOI":"10.1007\/978-94-011-5014-9_23","volume-title":"Learning in Graphical Models","author":"CK Williams","year":"1998","unstructured":"Williams, C.K.: Prediction with Gaussian processes: from linear regression to linear prediction and beyond. In: Jordan, M.I. (ed.) Learning in Graphical Models. NATO ASI Series (Series D: Behavioural and Social Sciences), vol. 89, pp. 599\u2013621. Springer, Dordrecht (1998). https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1007\/978-94-011-5014-9_23"},{"key":"29_CR42","doi-asserted-by":"crossref","unstructured":"Yang, F., Choi, W., Lin, Y.: Exploit all the layers: fast and accurate CNN object detector with scale dependent pooling and cascaded rejection classifiers. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Las Vegas, NV, pp. 2129\u20132137, June 2016","DOI":"10.1109\/CVPR.2016.234"},{"key":"29_CR43","doi-asserted-by":"crossref","unstructured":"Young-Chul, Y., Abhijeet, B., Kwangjin, Y., Moongu, J.: Online multi-object tracking with historical appearance matching and scene adaptive detection filtering. CoRR abs\/1805.10916 (2018)","DOI":"10.1109\/AVSS.2018.8639078"},{"key":"29_CR44","doi-asserted-by":"crossref","unstructured":"Yu, S., Lee, H., Kim, J.: Street crossing aid using light-weight CNNs for the visually impaired. In: Proceedings of the IEEE International Conference on Computer Vision Workshops, October 2019","DOI":"10.1109\/ICCVW.2019.00317"},{"key":"29_CR45","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"379","DOI":"10.1007\/978-3-030-01228-1_23","volume-title":"Computer Vision \u2013 ECCV 2018","author":"J Zhu","year":"2018","unstructured":"Zhu, J., Yang, H., Liu, N., Kim, M., Zhang, W., Yang, M.-H.: Online multi-object tracking with dual matching attention networks. In: Ferrari, V., Hebert, M., Sminchisescu, C., Weiss, Y. (eds.) ECCV 2018. LNCS, vol. 11209, pp. 379\u2013396. Springer, Cham (2018). https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1007\/978-3-030-01228-1_23"}],"container-title":["Lecture Notes in Computer Science","Computer Vision \u2013 ECCV 2020 Workshops"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-66823-5_29","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T19:25:17Z","timestamp":1735759517000},"score":1,"resource":{"primary":{"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/link.springer.com\/10.1007\/978-3-030-66823-5_29"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030668228","9783030668235"],"references-count":45,"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1007\/978-3-030-66823-5_29","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"3 January 2021","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:\/\/2.zoppoz.workers.dev:443\/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)"}}]}}