{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T07:33:11Z","timestamp":1742974391891,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":24,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819947416"},{"type":"electronic","value":"9789819947423"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"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":[[2023]]},"DOI":"10.1007\/978-981-99-4742-3_33","type":"book-chapter","created":{"date-parts":[[2023,7,30]],"date-time":"2023-07-30T00:02:38Z","timestamp":1690675358000},"page":"401-412","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Convolutional Self-attention Guided Graph Neural Network for Few-Shot Action Recognition"],"prefix":"10.1007","author":[{"given":"Fei","family":"Pan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jie","family":"Guo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yanwen","family":"Guo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,7,30]]},"reference":[{"key":"33_CR1","doi-asserted-by":"crossref","unstructured":"Ou, Y., Mi, L., Chen, Z.: Object-relation reasoning graph for action recognition. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 20101\u2013 20110. IEEE (2022)","DOI":"10.1109\/CVPR52688.2022.01950"},{"key":"33_CR2","doi-asserted-by":"publisher","first-page":"627","DOI":"10.1007\/978-3-031-20062-5_36","volume-title":"Computer Vision \u2013 ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23\u201327, 2022, Proceedings, Part III","author":"W Xiang","year":"2022","unstructured":"Xiang, W., Li, C., Wang, B., Wei, X., Hua, X.-S., Zhang, L.: Spatiotemporal self-attention modeling with\u00a0temporal patch shift for\u00a0action recognition. In: Avidan, S., Brostow, G., Ciss\u00e9, M., Farinella, G.M., Hassner, T. (eds.) Computer Vision \u2013 ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23\u201327, 2022, Proceedings, Part III, pp. 627\u2013644. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-20062-5_36"},{"key":"33_CR3","doi-asserted-by":"crossref","unstructured":"Zhang, H., Zhang, L., Qi, X., Li, H., Torr, P.H.S., Koniusz, P.: Few-shot action recognition with permutation-invariant attention. In: Proceedings of the European Conference on Computer Vision, Glasgow, UK (2020)","DOI":"10.1007\/978-3-030-58558-7_31"},{"issue":"1","key":"33_CR4","first-page":"273","volume":"44","author":"L Zhu","year":"2022","unstructured":"Zhu, L., Yang, Y.: Label independent memory for semi-supervised few-shot video classification. IEEE Trans. Pattern Anal. Mach. Intell. 44(1), 273\u2013285 (2022)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"33_CR5","doi-asserted-by":"crossref","unstructured":"Cao, K., Ji, J., Cao, Z., Chang, C., Niebles, J.C.: Few-shot video classification via temporal alignment. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, Seattle, WA, USA, pp. 10615\u201310624 (2020)","DOI":"10.1109\/CVPR42600.2020.01063"},{"key":"33_CR6","doi-asserted-by":"crossref","unstructured":"Wu, J., Zhang, T., Zhang, Z., Wu, F., Zhang, Y.: Motion-modulated temporal fragment alignment network for few-shot action recognition. In: IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 9141\u20139150. IEEE (2022)","DOI":"10.1109\/CVPR52688.2022.00894"},{"issue":"1","key":"33_CR7","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1109\/TASSP.1978.1163055","volume":"26","author":"H Sakoe","year":"1978","unstructured":"Sakoe, H., Chiba, S.: Dynamic programming algorithm optimization for spoken word recognition. IEEE Trans. Acoust. Speech Signal Process. 26(1), 43\u201349 (1978)","journal-title":"IEEE Trans. Acoust. Speech Signal Process."},{"key":"33_CR8","unstructured":"Vaswani, A., et al.: Attention is all you need. In: Advances in Neural Information Processing Systems, pp. 5998\u20136008 (2017)"},{"key":"33_CR9","unstructured":"Li, S., et al.: Enhancing the locality and breaking the memory bottleneck of transformer on time series forecasting. In: Advances in Neural Information Processing Systems, pp. 5243\u2013 5253 (2019)"},{"key":"33_CR10","unstructured":"Zhu, Z., Wang, L., Guo, S., Wu, G.: A closer look at few-shot video classification: a new baseline and benchmark. In: Proceedings of British Machine Vision Conference, BMVA Press (2021)"},{"key":"33_CR11","doi-asserted-by":"crossref","unstructured":"Li, S., et al.: Ta2n: two-stage action alignment network for few-shot action recognition. In: Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, AAAI Press (2022)","DOI":"10.1609\/aaai.v36i2.20029"},{"key":"33_CR12","doi-asserted-by":"crossref","unstructured":"Fu, Y., Zhang, L., Wang, J., Fu, Y., Jiang, Y.: Depth guided adaptive meta-fusion network for few-shot video recognition. In: Proceedings of the 28th ACM International Conference on Multimedia, Seattle, WA, USA. pp. 1142\u20131151. ACM (2020)","DOI":"10.1145\/3394171.3413502"},{"key":"33_CR13","doi-asserted-by":"crossref","unstructured":"Zhang, S., Zhou, J., He, X.: Learning implicit temporal alignment for few-shot video classification. In: Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, Montreal, Canada, pp. 1309\u20131315. ijcai.org (2021)","DOI":"10.24963\/ijcai.2021\/181"},{"key":"33_CR14","doi-asserted-by":"crossref","unstructured":"Perrett, T., Masullo, A., Burghardt, T., Mirmehdi, M., Damen, D.: Temporal-relational crosstransformers for few-shot action recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 475\u2013484. IEEE (2021)","DOI":"10.1109\/CVPR46437.2021.00054"},{"key":"33_CR15","unstructured":"Zhu, X., Toisoul, A., P\u00e9rez-R\u00faa, J., Zhang, L., Mart\u00ednez, B., Xiang, T.: Few-shot action recognition with prototype-centered attentive learning. In: Proceedings of the British Machine Vision Conference, BMVA Press (2021)"},{"key":"33_CR16","doi-asserted-by":"publisher","first-page":"471","DOI":"10.1007\/978-3-031-20044-1_27","volume-title":"Computer Vision \u2013 ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23\u201327, 2022, Proceedings, Part XX","author":"KD Nguyen","year":"2022","unstructured":"Nguyen, K.D., Tran, Q.-H., Nguyen, K., Hua, B.-S., Nguyen, R.: Inductive and\u00a0transductive few-shot video classification via\u00a0appearance and\u00a0temporal alignments. In: Avidan, S., Brostow, G., Ciss\u00e9, M., Farinella, G.M., Hassner, T. (eds.) Computer Vision \u2013 ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23\u201327, 2022, Proceedings, Part XX, pp. 471\u2013487. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-20044-1_27"},{"key":"33_CR17","unstructured":"Vinyals, O., Blundell, C., Lillicrap, T., Kavukcuoglu, K., Wierstra, D.: Matching networks for one shot learning. In: Advances in Neural Information Processing Systems, Barcelona, Spain, pp. 3630\u20133638 (2016)"},{"key":"33_CR18","doi-asserted-by":"crossref","unstructured":"Wang, L., Xiong, Y., Wang, Z., Qiao, Y., Lin, D., Tang, X., Gool, L.V.: Temporal segment networks: towards good practices for deep action recognition. In: Proc. of the European Conference on Computer Vision, pp. 20\u201336 (2016)","DOI":"10.1007\/978-3-319-46484-8_2"},{"key":"33_CR19","unstructured":"Kipf, T.N., Welling, M.: Semi-supervised classification with graph convolutional networks. In: International Conference on Learning Representations (2017)"},{"key":"33_CR20","unstructured":"Kay, W., et al.: The kinetics human action video dataset. CoRR abs\/1705.06950 (2017)"},{"key":"33_CR21","doi-asserted-by":"crossref","unstructured":"Goyal, R., Kahou, S.E., Michalski, V., Materzynska, J., et al.: The \u201csomething something\u201d video database for learning and evaluating visual common sense. In: Proceedings of the IEEE International Conference on Computer Vision, Venice, Italy, pp. 5843\u20135851 (2017)","DOI":"10.1109\/ICCV.2017.622"},{"key":"33_CR22","unstructured":"Soomro, K., Zamir, A.R., Shah, M.: Ucf101: a dataset of 101 human actions classes from videos in the wild. CoRR abs\/1212.0402 (2012)"},{"key":"33_CR23","doi-asserted-by":"crossref","unstructured":"Kuehne, H., Jhuang, H., Garrote, E., Poggio, T.A., Serre, T.: Hmdb: a large video database for human motion recognition. In: Proceedings of the IEEE International Conference on Computer Vision, Barcelona, Spain, pp. 2556\u20132563 (2011)","DOI":"10.1109\/ICCV.2011.6126543"},{"key":"33_CR24","doi-asserted-by":"crossref","unstructured":"Deng, J., Dong, W., Socher, R., Li, L., Li, K., Li, F.: Imagenet: a large-scale hierarchical image database. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Miami, Florida, USA, pp. 248\u2013255 (2009)","DOI":"10.1109\/CVPR.2009.5206848"}],"container-title":["Lecture Notes in Computer Science","Advanced Intelligent Computing Technology and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-99-4742-3_33","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,8,1]],"date-time":"2023-08-01T23:27:46Z","timestamp":1690932466000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-99-4742-3_33"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9789819947416","9789819947423"],"references-count":24,"URL":"https:\/\/doi.org\/10.1007\/978-981-99-4742-3_33","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"30 July 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICIC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligent Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Zhengzhou","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10 August 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 August 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icic2023a","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.ic-icc.cn\/2023\/index.htm","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}