{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T03:15:15Z","timestamp":1742958915707,"version":"3.40.3"},"publisher-location":"Cham","reference-count":13,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030654139"},{"type":"electronic","value":"9783030654146"}],"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\/978-3-030-65414-6_2","type":"book-chapter","created":{"date-parts":[[2021,1,4]],"date-time":"2021-01-04T08:03:24Z","timestamp":1609747404000},"page":"11-18","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Implementing Planning KL-Divergence"],"prefix":"10.1007","author":[{"given":"Jonah","family":"Philion","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Amlan","family":"Kar","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sanja","family":"Fidler","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,1,5]]},"reference":[{"key":"2_CR1","unstructured":"Nvidia drive constellation. https:\/\/www.nvidia.com\/en-us\/self-driving-cars\/drive-constellation\/. Accessed 14 Oct 2019"},{"key":"2_CR2","doi-asserted-by":"crossref","unstructured":"Bansal, M., Krizhevsky, A., Ogale, A.S.: Chauffeurnet: Learning to drive by imitating the best and synthesizing the worst. CoRR abs\/1812.03079 (2018). http:\/\/arxiv.org\/abs\/1812.03079","DOI":"10.15607\/RSS.2019.XV.031"},{"key":"2_CR3","unstructured":"Caesar, H., et al.: nuscenes: A multimodal dataset for autonomous driving. CoRR abs\/1903.11027 (2019). http:\/\/arxiv.org\/abs\/1903.11027"},{"key":"2_CR4","unstructured":"Dosovitskiy, A., Ros, G., Codevilla, F., Lopez, A., Koltun, V.: CARLA: An open urban driving simulator. In: Proceedings of the 1st Annual Conference on Robot Learning, pp. 1\u201316 (2017)"},{"key":"2_CR5","doi-asserted-by":"crossref","unstructured":"Kar, A., et al.: Meta-Sim: learning to generate synthetic datasets. In: ICCV (2019). http:\/\/arxiv.org\/abs\/1904.11621","DOI":"10.1109\/ICCV.2019.00465"},{"key":"2_CR6","doi-asserted-by":"crossref","unstructured":"Manivasagam, S., et al.: LiDARsim: Realistic LiDAR simulation by leveraging the real world (2020)","DOI":"10.1109\/CVPR42600.2020.01118"},{"key":"2_CR7","doi-asserted-by":"crossref","unstructured":"Mao, H., Yang, X., Dally, W.J.: A delay metric for video object detection: What average precision fails to tell (2019)","DOI":"10.1109\/ICCV.2019.00066"},{"key":"2_CR8","doi-asserted-by":"crossref","unstructured":"Philion, J., Kar, A., Fidler, S.: Learning to evaluate perception models using planner-centric metrics (2020)","DOI":"10.1109\/CVPR42600.2020.01407"},{"key":"2_CR9","unstructured":"Szegedy, C., et al.: Intriguing properties of neural networks (2013)"},{"key":"2_CR10","doi-asserted-by":"crossref","unstructured":"Yang, Z., et al.: SurfelGAN: Synthesizing realistic sensor data for autonomous driving (2020)","DOI":"10.1109\/CVPR42600.2020.01113"},{"key":"2_CR11","unstructured":"Zemel, R., Wu, Y., Swersky, K., Pitassi, T., Dwork, C.: Learning fair representations. In: Dasgupta, S., McAllester, D. (eds.) ICML, Proceedings of Machine Learning Research, Vol. 28, pp. 325\u2013333. PMLR, Atlanta, Georgia, USA (17\u201319 Jun 2013). http:\/\/proceedings.mlr.press\/v28\/zemel13.html"},{"key":"2_CR12","doi-asserted-by":"crossref","unstructured":"Zeng, W., et al.: End-to-end interpretable neural motion planner. In: CVPR (June 2019)","DOI":"10.1109\/CVPR.2019.00886"},{"key":"2_CR13","unstructured":"Zhu, B., Jiang, Z., Zhou, X., Li, Z., Yu, G.: Class-balanced grouping and sampling for point cloud 3d object detection (2019)"}],"container-title":["Lecture Notes in Computer Science","Computer Vision \u2013 ECCV 2020 Workshops"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-65414-6_2","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,4]],"date-time":"2025-01-04T00:03:14Z","timestamp":1735948994000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-65414-6_2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030654139","9783030654146"],"references-count":13,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-65414-6_2","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":"5 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:\/\/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)"}}]}}