{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,23]],"date-time":"2025-08-23T19:10:08Z","timestamp":1755976208278,"version":"3.44.0"},"publisher-location":"New York, NY, USA","reference-count":40,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,10,20]],"date-time":"2023-10-20T00:00:00Z","timestamp":1697760000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Key Projects of Key R&D Program of Jiangsu Province","award":["BE2020006, BE2020006-1"],"award-info":[{"award-number":["BE2020006, BE2020006-1"]}]},{"DOI":"10.13039\/501100006374","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62233003, 62073072"],"award-info":[{"award-number":["62233003, 62073072"]}],"id":[{"id":"10.13039\/501100006374","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Shenzhen Science and Technology Program","award":["JCYJ20210324132202005, JCYJ20220818101206014"],"award-info":[{"award-number":["JCYJ20210324132202005, JCYJ20220818101206014"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,10,20]]},"DOI":"10.1145\/3633624.3633635","type":"proceedings-article","created":{"date-parts":[[2024,1,29]],"date-time":"2024-01-29T06:38:38Z","timestamp":1706510318000},"page":"75-81","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Integrating Dual-Stream Cross Fusion and Ambiguous Exclude Contrastive Learning for Enhanced Human Action Recognition"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-8628-5839","authenticated-orcid":false,"given":"Biaozhang","family":"Huang","sequence":"first","affiliation":[{"name":"Southeast University, China and Nanjing Center for Applied Mathematics, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1529-4537","authenticated-orcid":false,"given":"Xinde","family":"Li","sequence":"additional","affiliation":[{"name":"Southeast University, China and Nanjing Center for Applied Mathematics, China"}]}],"member":"320","published-online":{"date-parts":[[2024,1,29]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.18178\/joig.11.1.72-81"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.18178\/joig.3.2.96-101"},{"key":"e_1_3_2_1_3_1","volume-title":"Remixmatch: Semi-supervised learning with distribution alignment and augmentation anchoring. arXiv preprint arXiv:1911.09785","author":"Berthelot David","year":"2019","unstructured":"David Berthelot, Nicholas Carlini, Ekin\u00a0D Cubuk, Alex Kurakin, Kihyuk Sohn, Han Zhang, and Colin Raffel. 2019. Remixmatch: Semi-supervised learning with distribution alignment and augmentation anchoring. arXiv preprint arXiv:1911.09785 (2019)."},{"key":"e_1_3_2_1_4_1","volume-title":"Unsupervised learning of visual features by contrasting cluster assignments. Advances in neural information processing systems 33","author":"Caron Mathilde","year":"2020","unstructured":"Mathilde Caron, Ishan Misra, Julien Mairal, Priya Goyal, Piotr Bojanowski, and Armand Joulin. 2020. Unsupervised learning of visual features by contrasting cluster assignments. Advances in neural information processing systems 33 (2020), 9912\u20139924."},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.rcim.2021.102258"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/TFUZZ.2021.3079495"},{"key":"e_1_3_2_1_7_1","first-page":"281","article-title":"Semi-supervised learning by entropy minimization","volume":"367","author":"Grandvalet Yves","year":"2005","unstructured":"Yves Grandvalet and Yoshua Bengio. 2005. Semi-supervised learning by entropy minimization. CAP 367 (2005), 281\u2013296.","journal-title":"CAP"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2018.8594452"},{"key":"e_1_3_2_1_9_1","volume-title":"Contrastive learning from extremely augmented skeleton sequences for self-supervised action recognition. 36, 1","author":"Guo Tianyu","year":"2022","unstructured":"Tianyu Guo, Hong Liu, Zhan Chen, Mengyuan Liu, Tao Wang, and Runwei Ding. 2022. Contrastive learning from extremely augmented skeleton sequences for self-supervised action recognition. 36, 1 (2022), 762\u2013770."},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.12720\/joig.2.1.28-32"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00975"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i1.19998"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19772-7_13"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-017-4979-0"},{"key":"e_1_3_2_1_15_1","volume-title":"Anticipating human activities using object affordances for reactive robotic response","author":"Koppula S","year":"2015","unstructured":"Hema\u00a0S Koppula and Ashutosh Saxena. 2015. Anticipating human activities using object affordances for reactive robotic response. IEEE transactions on pattern analysis and machine intelligence 38, 1 (2015), 14\u201329."},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.18178\/joig.6.2.174-180"},{"key":"e_1_3_2_1_17_1","volume-title":"Workshop on challenges in representation learning, ICML, Vol.\u00a03. Atlanta, 896","author":"Lee Dong-Hyun","year":"2013","unstructured":"Dong-Hyun Lee 2013. Pseudo-label: The simple and efficient semi-supervised learning method for deep neural networks. In Workshop on challenges in representation learning, ICML, Vol.\u00a03. Atlanta, 896."},{"key":"e_1_3_2_1_18_1","volume-title":"ESUAV-NI: Endogenous Security Framework for UAV Perception System Based on Neural Immunity","author":"Li Heqing","year":"2023","unstructured":"Heqing Li, Xinde Li, Zhentong Zhang, Chuanfei Hu, Fir Dunkin, and Shuzhi\u00a0Sam Ge. 2023. ESUAV-NI: Endogenous Security Framework for UAV Perception System Based on Neural Immunity. IEEE Transactions on Industrial Informatics (2023)."},{"key":"e_1_3_2_1_19_1","volume-title":"Iterative semi-supervised action recognition. arXiv preprint arXiv:2006.06911","author":"Li Jingyuan","year":"2020","unstructured":"Jingyuan Li and Eli Shlizerman. 2020. Iterate & cluster: Iterative semi-supervised action recognition. arXiv preprint arXiv:2006.06911 (2020)."},{"key":"e_1_3_2_1_20_1","volume-title":"Sparse semi-supervised action recognition with active learning. arXiv preprint arXiv:2012.01740","author":"Li Jingyuan","year":"2020","unstructured":"Jingyuan Li and Eli Shlizerman. 2020. Sparse semi-supervised action recognition with active learning. arXiv preprint arXiv:2012.01740 (2020)."},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2019.00123"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/3394171.3413548"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-20062-5_42"},{"key":"e_1_3_2_1_24_1","volume-title":"Virtual adversarial training: a regularization method for supervised and semi-supervised learning","author":"Miyato Takeru","year":"2018","unstructured":"Takeru Miyato, Shin-ichi Maeda, Masanori Koyama, and Shin Ishii. 2018. Virtual adversarial training: a regularization method for supervised and semi-supervised learning. IEEE transactions on pattern analysis and machine intelligence 41, 8 (2018), 1979\u20131993."},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.115"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2021.107868"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00810"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2022.3222871"},{"key":"e_1_3_2_1_29_1","volume-title":"Proceedings, Part VII 16","author":"Si Chenyang","year":"2020","unstructured":"Chenyang Si, Xuecheng Nie, Wei Wang, Liang Wang, Tieniu Tan, and Jiashi Feng. 2020. Adversarial self-supervised learning for semi-supervised 3d action recognition. In Computer Vision\u2013ECCV 2020: 16th European Conference, Glasgow, UK, August 23\u201328, 2020, Proceedings, Part VII 16. Springer, 35\u201351."},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2022.3157033"},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1145\/3474085.3475307"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.82"},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.339"},{"key":"e_1_3_2_1_34_1","volume-title":"Learning multi-view interactional skeleton graph for action recognition","author":"Wang Minsi","year":"2020","unstructured":"Minsi Wang, Bingbing Ni, and Xiaokang Yang. 2020. Learning multi-view interactional skeleton graph for action recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence (2020)."},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00393"},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2022.3175605"},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.12328"},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01317"},{"key":"e_1_3_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.18178\/joig.6.1.21-26"},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00156"}],"event":{"name":"BDSIC 2023: 2023 5th International Conference on Big-data Service and Intelligent Computation","acronym":"BDSIC 2023","location":"Singapore Singapore"},"container-title":["Proceedings of the 2023 5th International Conference on Big-data Service and Intelligent Computation"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3633624.3633635","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3633624.3633635","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,23]],"date-time":"2025-08-23T18:38:02Z","timestamp":1755974282000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3633624.3633635"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10,20]]},"references-count":40,"alternative-id":["10.1145\/3633624.3633635","10.1145\/3633624"],"URL":"https:\/\/doi.org\/10.1145\/3633624.3633635","relation":{},"subject":[],"published":{"date-parts":[[2023,10,20]]},"assertion":[{"value":"2024-01-29","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}