{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,17]],"date-time":"2026-03-17T09:00:44Z","timestamp":1773738044629,"version":"3.50.1"},"publisher-location":"Cham","reference-count":33,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030585761","type":"print"},{"value":"9783030585778","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:\/\/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\/978-3-030-58577-8_14","type":"book-chapter","created":{"date-parts":[[2020,9,23]],"date-time":"2020-09-23T14:04:27Z","timestamp":1600869867000},"page":"222-238","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":47,"title":["An Asymmetric Modeling for Action Assessment"],"prefix":"10.1007","author":[{"given":"Jibin","family":"Gao","sequence":"first","affiliation":[]},{"given":"Wei-Shi","family":"Zheng","sequence":"additional","affiliation":[]},{"given":"Jia-Hui","family":"Pan","sequence":"additional","affiliation":[]},{"given":"Chengying","family":"Gao","sequence":"additional","affiliation":[]},{"given":"Yaowei","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Wei","family":"Zeng","sequence":"additional","affiliation":[]},{"given":"Jianhuang","family":"Lai","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,9,24]]},"reference":[{"key":"14_CR1","unstructured":"Bertasius, G., Soo Park, H., Yu, S.X., Shi, J.: Am i a baller? basketball performance assessment from first-person videos. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 2177\u20132185 (2017)"},{"key":"14_CR2","doi-asserted-by":"crossref","unstructured":"Carreira, J., Zisserman, A.: Quo vadis, action recognition? a new model and the kinetics dataset. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 6299\u20136308 (2017)","DOI":"10.1109\/CVPR.2017.502"},{"key":"14_CR3","doi-asserted-by":"crossref","unstructured":"Chen, J., Wang, Y., Qin, J., Liu, L., Shao, L.: Fast person re-identification via cross-camera semantic binary transformation. In: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 2017","DOI":"10.1109\/CVPR.2017.566"},{"key":"14_CR4","unstructured":"Doughty, H., Damen, D., Mayol-Cuevas, W.: Who\u015b better, who\u015b best: skill determination in video using deep ranking. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2018)"},{"key":"14_CR5","doi-asserted-by":"crossref","unstructured":"Doughty, H., Mayol-Cuevas, W., Damen, D.: The pros and cons: Rank-aware temporal attention for skill determination in long videos, June 2019","DOI":"10.1109\/CVPR.2019.00805"},{"key":"14_CR6","unstructured":"Gao, Y., et al.: Jhu-isi gesture and skill assessment working set (jigsaws): a surgical activity dataset for human motion modeling. In: MICCAI Workshop: M2CAI, vol. 3, p. 3 (2014)"},{"key":"14_CR7","doi-asserted-by":"crossref","unstructured":"Gattupalli, S., Ebert, D., Papakostas, M., Makedon, F., Athitsos, V.: Cognilearn: a deep learning-based interface for cognitive behavior assessment. In: Proceedings of the 22nd International Conference on Intelligent User Interfaces, pp. 577\u2013587. ACM (2017)","DOI":"10.1145\/3025171.3025213"},{"key":"14_CR8","doi-asserted-by":"crossref","unstructured":"Gers, F.A., Schmidhuber, J., Cummins, F.: Learning to forget: Continual prediction with LSTM. In: IET Conference Proceedings, vol. 5, pp. 850\u2013855, January 1999","DOI":"10.1049\/cp:19991218"},{"key":"14_CR9","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"523","DOI":"10.1007\/978-3-540-45243-0_67","volume-title":"Pattern Recognition","author":"W Ilg","year":"2003","unstructured":"Ilg, W., Mezger, J., Giese, M.: Estimation of skill levels in sports based on hierarchical spatio-temporal correspondences. In: Michaelis, B., Krell, G. (eds.) DAGM 2003. LNCS, vol. 2781, pp. 523\u2013531. Springer, Heidelberg (2003). https:\/\/doi.org\/10.1007\/978-3-540-45243-0_67"},{"key":"14_CR10","doi-asserted-by":"crossref","unstructured":"Li, H., Cai, Y., Zheng, W.S.: Deep dual relation modeling for egocentric interaction recognition. In: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 2019","DOI":"10.1109\/CVPR.2019.00812"},{"key":"14_CR11","doi-asserted-by":"crossref","unstructured":"Li, W.H., Hong, F.T., Zheng, W.S.: Learning to learn relation for important people detection in still images. In: Computer Vision and Pattern Recognition (2019)","DOI":"10.1109\/CVPR.2019.00514"},{"key":"14_CR12","doi-asserted-by":"crossref","unstructured":"Li, W.H., Li, B., Zheng, W.S.: Personrank: detecting important people in images. In: International Conference on Automatic Face & Gesture Recognition (FG 2018) (2018)","DOI":"10.1109\/FG.2018.00042"},{"key":"14_CR13","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"138","DOI":"10.1007\/978-3-319-07521-1_15","volume-title":"Information Processing in Computer-Assisted Interventions","author":"A Malpani","year":"2014","unstructured":"Malpani, A., Vedula, S.S., Chen, C.C.G., Hager, G.D.: Pairwise comparison-based objective score for automated skill assessment of segments in a surgical task. In: Stoyanov, D., Collins, D.L., Sakuma, I., Abolmaesumi, P., Jannin, P. (eds.) IPCAI 2014. LNCS, vol. 8498, pp. 138\u2013147. Springer, Cham (2014). https:\/\/doi.org\/10.1007\/978-3-319-07521-1_15"},{"key":"14_CR14","doi-asserted-by":"crossref","unstructured":"Paiement, A., Tao, L., Hannuna, S., Camplani, M., Damen, D., Mirmehdi, M.: Online quality assessment of human movement from skeleton data. In: British Machine Vision Conference, pp. 153\u2013166. BMVA Press (2014)","DOI":"10.5244\/C.28.79"},{"key":"14_CR15","doi-asserted-by":"crossref","unstructured":"Pan, J.H., Gao, J., Zheng, W.S.: Action assessment by joint relation graphs. In: The IEEE International Conference on Computer Vision (ICCV), October 2019","DOI":"10.1109\/ICCV.2019.00643"},{"key":"14_CR16","doi-asserted-by":"crossref","unstructured":"Parmar, P., Morris, B.T.: What and how well you performed? a multitask learning approach to action quality assessment. In: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 2019","DOI":"10.1109\/CVPR.2019.00039"},{"key":"14_CR17","doi-asserted-by":"crossref","unstructured":"Parmar, P., Tran Morris, B.: Learning to score olympic events. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp. 20\u201328 (2017)","DOI":"10.1109\/CVPRW.2017.16"},{"key":"14_CR18","doi-asserted-by":"publisher","unstructured":"Parmar, P., Tran Morris, B.: Action quality assessment across multiple actions. In: 2019 IEEE Winter Conference on Applications of Computer Vision (WACV), pp. 1468\u20131476, January 2019. https:\/\/doi.org\/10.1109\/WACV.2019.00161","DOI":"10.1109\/WACV.2019.00161"},{"key":"14_CR19","doi-asserted-by":"crossref","unstructured":"P\u00e9rez, J.S., Meinhardt-Llopis, E., Facciolo, G.: Tv-l1 optical flow estimation. Image Processing On Line, pp. 137\u2013150 (2013)","DOI":"10.5201\/ipol.2013.26"},{"key":"14_CR20","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"556","DOI":"10.1007\/978-3-319-10599-4_36","volume-title":"Computer Vision \u2013 ECCV 2014","author":"H Pirsiavash","year":"2014","unstructured":"Pirsiavash, H., Vondrick, C., Torralba, A.: Assessing the quality of actions. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.) ECCV 2014. LNCS, vol. 8694, pp. 556\u2013571. Springer, Cham (2014). https:\/\/doi.org\/10.1007\/978-3-319-10599-4_36"},{"issue":"1","key":"14_CR21","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1109\/TNN.2008.2005605","volume":"20","author":"F Scarselli","year":"2009","unstructured":"Scarselli, F., Gori, M., Tsoi, A.C., Hagenbuchner, M., Monfardini, G.: The graph neural network model. IEEE Trans. Neural Netw. 20(1), 61\u201380 (2009)","journal-title":"IEEE Trans. Neural Netw."},{"key":"14_CR22","unstructured":"Sharma, Y., et al.: Video based assessment of osats using sequential motion textures. Georgia Institute of Technology (2014)"},{"key":"14_CR23","doi-asserted-by":"crossref","unstructured":"Solomon Mathialagan, C., Gallagher, A.C., Batra, D.: VIP: finding important people in images. In: Computer Vision and Pattern Recognition (2015)","DOI":"10.1109\/CVPR.2015.7299119"},{"key":"14_CR24","unstructured":"Vaswani, A., et al.: Attention is all you need. In: Advances in Neural Information Processing Systems 30, pp. 5998\u20136008. Curran Associates, Inc. (2017). http:\/\/papers.nips.cc\/paper\/7181-attention-is-all-you-need.pdf"},{"key":"14_CR25","doi-asserted-by":"crossref","unstructured":"Wang, Z., Lu, J., Tao, C., Zhou, J., Tian, Q.: Learning channel-wise interactions for binary convolutional neural networks. In: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 2019","DOI":"10.1109\/CVPR.2019.00066"},{"key":"14_CR26","unstructured":"Xu, C., Fu, Y., Zhang, B., Chen, Z., Jiang, Y.G., Xue, X.: Learning to score the figure skating sports videos. arXiv preprint arXiv:1802.02774 (2018)"},{"key":"14_CR27","doi-asserted-by":"crossref","unstructured":"Yan, S., Xiong, Y., Lin, D.: Spatial temporal graph convolutional networks for skeleton-based action recognition. In: Thirty-Second AAAI Conference on Artificial Intelligence (2018)","DOI":"10.1609\/aaai.v32i1.12328"},{"key":"14_CR28","doi-asserted-by":"crossref","unstructured":"Zhang, Q., Li, B.: Video-based motion expertise analysis in simulation-based surgical training using hierarchical dirichlet process hidden markov model. In: Proceedings of the 2011 international ACM workshop on Medical multimedia analysis and retrieval, pp. 19\u201324. ACM (2011)","DOI":"10.1145\/2072545.2072550"},{"issue":"6","key":"14_CR29","doi-asserted-by":"publisher","first-page":"1206","DOI":"10.1109\/TPAMI.2014.2361121","volume":"37","author":"Q Zhang","year":"2015","unstructured":"Zhang, Q., Li, B.: Relative hidden markov models for video-based evaluation of motion skills in surgical training. IEEE transactions on pattern analysis and machine intelligence 37(6), 1206\u20131218 (2015)","journal-title":"IEEE transactions on pattern analysis and machine intelligence"},{"key":"14_CR30","doi-asserted-by":"publisher","first-page":"731","DOI":"10.1007\/s11548-018-1735-5","volume":"13","author":"A Zia","year":"2018","unstructured":"Zia, A., Essa, I.: Automated surgical skill assessment in RMIS training. Int J CARS 13, 731\u2013739 (2018)","journal-title":"Int J CARS"},{"key":"14_CR31","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"430","DOI":"10.1007\/978-3-319-24553-9_53","volume-title":"Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2015","author":"A Zia","year":"2015","unstructured":"Zia, A., Sharma, Y., Bettadapura, V., Sarin, E.L., Clements, M.A., Essa, I.: Automated assessment of surgical skills using frequency analysis. In: Navab, N., Hornegger, J., Wells, W.M., Frangi, A.F. (eds.) MICCAI 2015. LNCS, vol. 9349, pp. 430\u2013438. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-24553-9_53"},{"issue":"3","key":"14_CR32","doi-asserted-by":"publisher","first-page":"443","DOI":"10.1007\/s11548-018-1704-z","volume":"13","author":"A Zia","year":"2018","unstructured":"Zia, A., Sharma, Y., Bettadapura, V., Sarin, E.L., Essa, I.: Video and accelerometer-based motion analysis for automated surgical skills assessment. Int. J. Comput. Assisted Radiol. Surgery 13(3), 443\u2013455 (2018)","journal-title":"Int. J. Comput. Assisted Radiol. Surgery"},{"issue":"9","key":"14_CR33","doi-asserted-by":"publisher","first-page":"1623","DOI":"10.1007\/s11548-016-1468-2","volume":"11","author":"A Zia","year":"2016","unstructured":"Zia, A., et al.: Automated video-based assessment of surgical skills for training and evaluation in medical schools. Int. J. Comput. Assisted Radiol. Surgery 11(9), 1623\u20131636 (2016)","journal-title":"Int. J. Comput. Assisted Radiol. Surgery"}],"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\/978-3-030-58577-8_14","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,23]],"date-time":"2024-09-23T00:04:22Z","timestamp":1727049862000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-58577-8_14"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030585761","9783030585778"],"references-count":33,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-58577-8_14","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":"24 September 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.","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)"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}