{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T18:02:39Z","timestamp":1743012159592,"version":"3.40.3"},"publisher-location":"Cham","reference-count":33,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031783531"},{"type":"electronic","value":"9783031783548"}],"license":[{"start":{"date-parts":[[2024,12,4]],"date-time":"2024-12-04T00:00:00Z","timestamp":1733270400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,12,4]],"date-time":"2024-12-04T00:00:00Z","timestamp":1733270400000},"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\/978-3-031-78354-8_16","type":"book-chapter","created":{"date-parts":[[2024,12,3]],"date-time":"2024-12-03T10:30:35Z","timestamp":1733221835000},"page":"245-261","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["EchoGCN: An Echo Graph Convolutional Network for Skeleton-Based Action Recognition"],"prefix":"10.1007","author":[{"given":"Weiwen","family":"Qian","sequence":"first","affiliation":[]},{"given":"Qian","family":"Huang","sequence":"additional","affiliation":[]},{"given":"Chang","family":"Li","sequence":"additional","affiliation":[]},{"given":"Zhongqi","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Yingchi","family":"Mao","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,12,4]]},"reference":[{"key":"16_CR1","doi-asserted-by":"publisher","first-page":"146","DOI":"10.1016\/j.cogsys.2018.04.002","volume":"50","author":"A Akula","year":"2018","unstructured":"Akula, A., Shah, A.K., Ghosh, R.: Deep learning approach for human action recognition in infrared images. Cogn. Syst. Res. 50, 146\u2013154 (2018)","journal-title":"Cogn. Syst. Res."},{"key":"16_CR2","doi-asserted-by":"crossref","unstructured":"Bai, R., Li, M., Meng, B., Li, F., Jiang, M., Ren, J., Sun, D.: Hierarchical graph convolutional skeleton transformer for action recognition. In: 2022 IEEE International Conference on Multimedia and Expo (ICME). pp. 01\u201306 (2022)","DOI":"10.1109\/ICME52920.2022.9859781"},{"key":"16_CR3","doi-asserted-by":"crossref","unstructured":"Chen, Y., Zhang, Z., Yuan, C., Li, B., Deng, Y., Hu, W.: Channel-wise topology refinement graph convolution for skeleton-based action recognition. In: 2021 IEEE\/CVF International Conference on Computer Vision (ICCV). pp. 13339\u201313348 (2021)","DOI":"10.1109\/ICCV48922.2021.01311"},{"key":"16_CR4","doi-asserted-by":"crossref","unstructured":"Cheng, K., Zhang, Y., He, X., Chen, W., Cheng, J., Lu, H.: Skeleton-based action recognition with shift graph convolutional network. In: 2020 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). pp. 180\u2013189 (2020)","DOI":"10.1109\/CVPR42600.2020.00026"},{"key":"16_CR5","doi-asserted-by":"publisher","first-page":"7333","DOI":"10.1109\/TIP.2021.3104182","volume":"30","author":"K Cheng","year":"2021","unstructured":"Cheng, K., Zhang, Y., He, X., Cheng, J., Lu, H.: Extremely lightweight skeleton-based action recognition with shiftgcn++. IEEE Trans. Image Process. 30, 7333\u20137348 (2021)","journal-title":"IEEE Trans. Image Process."},{"key":"16_CR6","doi-asserted-by":"crossref","unstructured":"Ch\u00e9ron, G., Laptev, I., Schmid, C.: P-cnn: Pose-based cnn features for action recognition. In: 2015 IEEE International Conference on Computer Vision (ICCV). pp. 3218\u20133226 (2015)","DOI":"10.1109\/ICCV.2015.368"},{"key":"16_CR7","doi-asserted-by":"crossref","unstructured":"Du, Y., Wang, W., Wang, L.: Hierarchical recurrent neural network for skeleton based action recognition. In: 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). pp. 1110\u20131118 (2015)","DOI":"10.1109\/CVPR.2015.7298714"},{"key":"16_CR8","doi-asserted-by":"crossref","unstructured":"Heo, B., Kim, J., Yun, S., Park, H., Kwak, N., Choi, J.Y.: A comprehensive overhaul of feature distillation. In: 2019 IEEE\/CVF International Conference on Computer Vision (ICCV). pp. 1921\u20131930 (2019)","DOI":"10.1109\/ICCV.2019.00201"},{"key":"16_CR9","doi-asserted-by":"crossref","unstructured":"Heo, B., Lee, M., Yun, S., Choi, J.Y.: Knowledge transfer via distillation of activation boundaries formed by hidden neurons. In: Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence (2019)","DOI":"10.1609\/aaai.v33i01.33013779"},{"key":"16_CR10","unstructured":"Hinton, G.E., Vinyals, O., Dean, J.: Distilling the knowledge in a neural network. ArXiv abs\/1503.02531 (2015)"},{"key":"16_CR11","doi-asserted-by":"publisher","first-page":"295","DOI":"10.1016\/j.patcog.2016.08.003","volume":"61","author":"A Jalal","year":"2017","unstructured":"Jalal, A., Kim, Y.H., Kim, Y.J., Kamal, S., Kim, D.: Robust human activity recognition from depth video using spatiotemporal multi-fused features. Pattern Recogn. 61, 295\u2013308 (2017)","journal-title":"Pattern Recogn."},{"issue":"11","key":"16_CR12","doi-asserted-by":"publisher","first-page":"3781","DOI":"10.1109\/TIP.2015.2456412","volume":"24","author":"YG Jiang","year":"2015","unstructured":"Jiang, Y.G., Dai, Q., Liu, W., Xue, X., Ngo, C.W.: Human action recognition in unconstrained videos by explicit motion modeling. IEEE Trans. Image Process. 24(11), 3781\u20133795 (2015)","journal-title":"IEEE Trans. Image Process."},{"key":"16_CR13","doi-asserted-by":"crossref","unstructured":"Karpathy, A., Toderici, G., Shetty, S., Leung, T., Sukthankar, R., Fei-Fei, L.: Large-scale video classification with convolutional neural networks. In: 2014 IEEE Conference on Computer Vision and Pattern Recognition. pp. 1725\u20131732 (2014)","DOI":"10.1109\/CVPR.2014.223"},{"key":"16_CR14","unstructured":"Kim, J., Park, S., Kwak, N.: Paraphrasing complex network: Network compression via factor transfer. In: Proceedings of the 32nd International Conference on Neural Information Processing Systems. p. 2765\u20132774 (2018)"},{"key":"16_CR15","doi-asserted-by":"crossref","unstructured":"Lee, I., Kim, D., Kang, S., Lee, S.: Ensemble deep learning for skeleton-based action recognition using temporal sliding lstm networks. In: 2017 IEEE International Conference on Computer Vision (ICCV). pp. 1012\u20131020 (2017)","DOI":"10.1109\/ICCV.2017.115"},{"key":"16_CR16","doi-asserted-by":"crossref","unstructured":"Li, C., Huang, Q., Mao, Y.: Dd-gcn: Directed diffusion graph convolutional network for skeleton-based human action recognition. In: 2023 IEEE International Conference on Multimedia and Expo (ICME). pp. 786\u2013791 (2015)","DOI":"10.1109\/ICME55011.2023.00140"},{"key":"16_CR17","doi-asserted-by":"crossref","unstructured":"Li, C., Mao, Y., Huang, Q., Zhu, X., Wu, J.: Scale-aware graph convolutional network with part-level refinement for skeleton-based human action recognition. IEEE Transactions on Circuits and Systems for Video Technology (2023)","DOI":"10.1109\/TCSVT.2023.3334872"},{"key":"16_CR18","doi-asserted-by":"crossref","unstructured":"Li, M., Chen, S., Chen, X., Zhang, Y., Wang, Y., Tian, Q.: Actional-structural graph convolutional networks for skeleton-based action recognition. In: 2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). pp. 3590\u20133598 (2019)","DOI":"10.1109\/CVPR.2019.00371"},{"issue":"10","key":"16_CR19","doi-asserted-by":"publisher","first-page":"2684","DOI":"10.1109\/TPAMI.2019.2916873","volume":"42","author":"J Liu","year":"2020","unstructured":"Liu, J., Shahroudy, A., Perez, M., Wang, G., Duan, L.Y., Kot, A.C.: Ntu rgb+d 120: A large-scale benchmark for 3d human activity understanding. IEEE Trans. Pattern Anal. Mach. Intell. 42(10), 2684\u20132701 (2020)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"16_CR20","doi-asserted-by":"crossref","unstructured":"Liu, Z., Zhang, H., Chen, Z., Wang, Z., Ouyang, W.: Disentangling and unifying graph convolutions for skeleton-based action recognition. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. pp. 143\u2013152 (2020)","DOI":"10.1109\/CVPR42600.2020.00022"},{"key":"16_CR21","doi-asserted-by":"crossref","unstructured":"Mehran, R., Oyama, A., Shah, M.: Abnormal crowd behavior detection using social force model. In: 2009 IEEE Conference on Computer Vision and Pattern Recognition. pp. 935\u2013942 (2009)","DOI":"10.1109\/CVPR.2009.5206641"},{"issue":"4","key":"16_CR22","doi-asserted-by":"publisher","first-page":"4783","DOI":"10.1109\/TNNLS.2022.3201518","volume":"35","author":"Z Qin","year":"2024","unstructured":"Qin, Z., Liu, Y., Ji, P., Kim, D., Wang, L., McKay, R.I., Anwar, S., Gedeon, T.: Fusing higher-order features in graph neural networks for skeleton-based action recognition. IEEE Transactions on Neural Networks and Learning Systems 35(4), 4783\u20134797 (2024)","journal-title":"IEEE Transactions on Neural Networks and Learning Systems"},{"key":"16_CR23","unstructured":"Romero, A., Ballas, N., Kahou, S.E., Chassang, A., Gatta, C., Bengio, Y.: Fitnets: Hints for thin deep nets. In: International Conference on Learning Representations (ICLR) (2015)"},{"key":"16_CR24","doi-asserted-by":"crossref","unstructured":"Shahroudy, A., Liu, J., Ng, T.T., Wang, G.: Ntu rgb+d: A large scale dataset for 3d human activity analysis. In: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). pp. 1010\u20131019 (2016)","DOI":"10.1109\/CVPR.2016.115"},{"key":"16_CR25","doi-asserted-by":"crossref","unstructured":"Shi, L., Zhang, Y., Cheng, J., Lu, H.: Two-stream adaptive graph convolutional networks for skeleton-based action recognition. In: 2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). pp. 12018\u201312027 (2019)","DOI":"10.1109\/CVPR.2019.01230"},{"key":"16_CR26","doi-asserted-by":"crossref","unstructured":"Si, C., Chen, W., Wang, W., Wang, L.: An attention enhanced graph convolutional lstm network for skeleton-based action recognition. In: IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). pp. 1227\u20131236 (2019)","DOI":"10.1109\/CVPR.2019.00132"},{"issue":"2","key":"16_CR27","doi-asserted-by":"publisher","first-page":"1474","DOI":"10.1109\/TPAMI.2022.3157033","volume":"45","author":"YF Song","year":"2023","unstructured":"Song, Y.F., Zhang, Z., Shan, C., Wang, L.: Constructing stronger and faster baselines for skeleton-based action recognition. IEEE Trans. Pattern Anal. Mach. Intell. 45(2), 1474\u20131488 (2023)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"16_CR28","doi-asserted-by":"crossref","unstructured":"Wang, J., Nie, X., Xia, Y., Wu, Y., Zhu, S.C.: Cross-view action modeling, learning, and recognition. In: Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition. p. 2649\u20132656 (2014)","DOI":"10.1109\/CVPR.2014.339"},{"issue":"4","key":"16_CR29","doi-asserted-by":"publisher","first-page":"2120","DOI":"10.1109\/TCSVT.2021.3085959","volume":"32","author":"C Wu","year":"2022","unstructured":"Wu, C., Wu, X.J., Kittler, J.: Graph2net: Perceptually-enriched graph learning for skeleton-based action recognition. IEEE Trans. Circuits Syst. Video Technol. 32(4), 2120\u20132132 (2022)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"16_CR30","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2024.110427","volume":"151","author":"Z Wu","year":"2024","unstructured":"Wu, Z., Ma, N., Wang, C., Xu, C., Xu, G., Li, M.: Spatial-temporal hypergraph based on dual-stage attention network for multi-view data lightweight action recognition. Pattern Recogn. 151, 110427 (2024)","journal-title":"Pattern Recogn."},{"key":"16_CR31","doi-asserted-by":"crossref","unstructured":"Yan, S., Xiong, Y., Lin, D.: Spatial temporal graph convolutional networks for skeleton-based action recognition. In: AAAI on Artificial Intelligence (2018)","DOI":"10.1609\/aaai.v32i1.12328"},{"key":"16_CR32","doi-asserted-by":"crossref","unstructured":"Yun, K., Honorio, J., Chattopadhyay, D., Berg, T.L., Samaras, D.: Two-person interaction detection using body-pose features and multiple instance learning. In: 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops. pp. 28\u201335 (2012)","DOI":"10.1109\/CVPRW.2012.6239234"},{"key":"16_CR33","unstructured":"Zagoruyko, S., Komodakis, N.: Paying more attention to attention: Improving the performance of convolutional neural networks via attention transfer. In: International Conference on Learning Representations (ICLR) (2017)"}],"container-title":["Lecture Notes in Computer Science","Pattern Recognition"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-78354-8_16","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,3]],"date-time":"2024-12-03T11:29:28Z","timestamp":1733225368000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-78354-8_16"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,4]]},"ISBN":["9783031783531","9783031783548"],"references-count":33,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-78354-8_16","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024,12,4]]},"assertion":[{"value":"4 December 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICPR","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Pattern Recognition","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Kolkata","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"India","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":"1 December 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 December 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icpr2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/icpr2024.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}