{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,25]],"date-time":"2025-05-25T18:10:04Z","timestamp":1748196604128,"version":"3.41.0"},"publisher-location":"Cham","reference-count":31,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031915741","type":"print"},{"value":"9783031915758","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"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\/978-3-031-91575-8_9","type":"book-chapter","created":{"date-parts":[[2025,5,25]],"date-time":"2025-05-25T17:57:08Z","timestamp":1748195828000},"page":"136-150","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Enhanced Action Quality Assessment with\u00a0Dual-Stream Pose and\u00a0Video Feature Integration"],"prefix":"10.1007","author":[{"given":"Yanting","family":"Zhang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xia","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenguang","family":"Zeng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shuai","family":"Yu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zijian","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhijun","family":"Fang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,5,12]]},"reference":[{"key":"9_CR1","doi-asserted-by":"publisher","unstructured":"Bai, Y., et al.: Action quality assessment with temporal parsing transformer. In: Avidan, S., Brostow, G., Ciss\u00e9, M., Farinella, G.M., Hassner, T. (eds.) ECCV 2022. LNCS, vol. 13664, pp. 422\u2013438. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-19772-7_25","DOI":"10.1007\/978-3-031-19772-7_25"},{"key":"9_CR2","doi-asserted-by":"crossref","unstructured":"Bertasius, G., Soo\u00a0Park, 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)","DOI":"10.1109\/ICCV.2017.239"},{"key":"9_CR3","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":"9_CR4","doi-asserted-by":"crossref","unstructured":"Dadashzadeh, A., Duan, S., Whone, A., Mirmehdi, M.: PECoP: parameter efficient continual pretraining for action quality assessment. In: Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision, pp. 42\u201352 (2024)","DOI":"10.1109\/WACV57701.2024.00012"},{"key":"9_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. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 7862\u20137871 (2019)","DOI":"10.1109\/CVPR.2019.00805"},{"key":"9_CR6","doi-asserted-by":"crossref","unstructured":"Duan, H., Zhao, Y., Chen, K., Lin, D., Dai, B.: Revisiting skeleton-based action recognition. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 2969\u20132978 (2022)","DOI":"10.1109\/CVPR52688.2022.00298"},{"key":"9_CR7","unstructured":"Kingma, D.P., Ba, J.: Adam: a method for stochastic optimization. arXiv preprint arXiv:1412.6980 (2014)"},{"issue":"2","key":"9_CR8","doi-asserted-by":"publisher","first-page":"468","DOI":"10.1109\/TNSRE.2020.2966249","volume":"28","author":"Y Liao","year":"2020","unstructured":"Liao, Y., Vakanski, A., Xian, M.: A deep learning framework for assessing physical rehabilitation exercises. IEEE Trans. Neural Syst. Rehabil. Eng. 28(2), 468\u2013477 (2020)","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"9_CR9","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., 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":"9_CR10","doi-asserted-by":"crossref","unstructured":"Nekoui, M., Cruz, F.O.T., Cheng, L.: FALCONS: fast learner-grader for contorted poses in sports. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops, pp. 900\u2013901 (2020)","DOI":"10.1109\/CVPRW50498.2020.00458"},{"key":"9_CR11","doi-asserted-by":"crossref","unstructured":"Nekoui, M., Cruz, F.O.T., Cheng, L.: EAGLE-Eye: extreme-pose action grader using detail bird\u2019s-eye view. In: Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision, pp. 394\u2013402 (2021)","DOI":"10.1109\/WACV48630.2021.00044"},{"key":"9_CR12","doi-asserted-by":"crossref","unstructured":"Pan, J.H., Gao, J., Zheng, W.S.: Action assessment by joint relation graphs. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 6331\u20136340 (2019)","DOI":"10.1109\/ICCV.2019.00643"},{"key":"9_CR13","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: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 304\u2013313 (2019)","DOI":"10.1109\/CVPR.2019.00039"},{"key":"9_CR14","doi-asserted-by":"crossref","unstructured":"Parmar, P., Reddy, J., Morris, B.: Piano skills assessment. In: 2021 IEEE 23rd International Workshop on Multimedia Signal Processing (MMSP), pp.\u00a01\u20135. IEEE (2021)","DOI":"10.1109\/MMSP53017.2021.9733638"},{"key":"9_CR15","doi-asserted-by":"crossref","unstructured":"Parmar, P., Tran\u00a0Morris, 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":"9_CR16","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"},{"key":"9_CR17","doi-asserted-by":"crossref","unstructured":"Shao, D., Zhao, Y., Dai, B., Lin, D.: Intra-and inter-action understanding via temporal action parsing. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 730\u2013739 (2020)","DOI":"10.1109\/CVPR42600.2020.00081"},{"key":"9_CR18","doi-asserted-by":"crossref","unstructured":"Sun, K., Xiao, B., Liu, D., Wang, J.: Deep high-resolution representation learning for human pose estimation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 5693\u20135703 (2019)","DOI":"10.1109\/CVPR.2019.00584"},{"key":"9_CR19","doi-asserted-by":"crossref","unstructured":"Tang, Y., et al.: Uncertainty-aware score distribution learning for action quality assessment. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 9839\u20139848 (2020)","DOI":"10.1109\/CVPR42600.2020.00986"},{"key":"9_CR20","doi-asserted-by":"crossref","unstructured":"Tran, D., Bourdev, L., Fergus, R., Torresani, L., Paluri, M.: Learning spatiotemporal features with 3D convolutional networks. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 4489\u20134497 (2015)","DOI":"10.1109\/ICCV.2015.510"},{"key":"9_CR21","unstructured":"Vaswani, A., et al.: Attention is all You need. In: Advances in Neural Information Processing Systems, vol. 30 (2017)"},{"key":"9_CR22","doi-asserted-by":"crossref","unstructured":"Wang, S., Yang, D., Zhai, P., Chen, C., Zhang, L.: TSA-Net: tube self-attention network for action quality assessment. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 4902\u20134910 (2021)","DOI":"10.1145\/3474085.3475438"},{"key":"9_CR23","doi-asserted-by":"crossref","unstructured":"Xu, A., Zeng, L.A., Zheng, W.S.: Likert scoring with grade decoupling for long-term action assessment. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 3232\u20133241 (2022)","DOI":"10.1109\/CVPR52688.2022.00323"},{"issue":"12","key":"9_CR24","doi-asserted-by":"publisher","first-page":"4578","DOI":"10.1109\/TCSVT.2019.2927118","volume":"30","author":"C Xu","year":"2019","unstructured":"Xu, C., Fu, Y., Zhang, B., Chen, Z., Jiang, Y.G., Xue, X.: Learning to score figure skating sport videos. IEEE Trans. Circuits Syst. Video Technol. 30(12), 4578\u20134590 (2019)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"9_CR25","doi-asserted-by":"crossref","unstructured":"Xu, J., Rao, Y., Yu, X., Chen, G., Zhou, J., Lu, J.: FineDiving: a fine-grained dataset for procedure-aware action quality assessment. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 2949\u20132958 (2022)","DOI":"10.1109\/CVPR52688.2022.00296"},{"key":"9_CR26","doi-asserted-by":"crossref","unstructured":"Yan, S., Xiong, Y., Lin, D.: Spatial temporal graph convolutional networks for Skeleton-based action recognition. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol.\u00a032 (2018)","DOI":"10.1609\/aaai.v32i1.12328"},{"key":"9_CR27","doi-asserted-by":"crossref","unstructured":"Yu, X., Rao, Y., Zhao, W., Lu, J., Zhou, J.: Group-aware contrastive regression for action quality assessment. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 7919\u20137928 (2021)","DOI":"10.1109\/ICCV48922.2021.00782"},{"issue":"6","key":"9_CR28","doi-asserted-by":"publisher","first-page":"1206","DOI":"10.1109\/TPAMI.2014.2361121","volume":"37","author":"Q Zhang","year":"2014","unstructured":"Zhang, Q., Li, B.: Relative hidden Markov models for video-based evaluation of motion skills in surgical training. IEEE Trans. Pattern Anal. Mach. Intell. 37(6), 1206\u20131218 (2014)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"9_CR29","doi-asserted-by":"crossref","unstructured":"Zhang, S., et al.: LOGO: a long-form video dataset for group action quality assessment. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 2405\u20132414 (2023)","DOI":"10.1109\/CVPR52729.2023.00238"},{"key":"9_CR30","unstructured":"Zhou, C., Huang, Y.: Uncertainty-driven action quality assessment. arXiv preprint arXiv:2207.14513 (2022)"},{"issue":"3","key":"9_CR31","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. Assist. Radiol. Surg. 13(3), 443\u2013455 (2018). https:\/\/doi.org\/10.1007\/s11548-018-1704-z","journal-title":"Int. J. Comput. Assist. Radiol. Surg."}],"container-title":["Lecture Notes in Computer Science","Computer Vision \u2013 ECCV 2024 Workshops"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-91575-8_9","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,25]],"date-time":"2025-05-25T17:57:18Z","timestamp":1748195838000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-91575-8_9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9783031915741","9783031915758"],"references-count":31,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-91575-8_9","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"12 May 2025","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"}}]}}