{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,10]],"date-time":"2026-08-10T03:28:22Z","timestamp":1786332502058,"version":"build-2736575974"},"reference-count":46,"publisher":"Springer Science and Business Media LLC","issue":"12","license":[{"start":{"date-parts":[[2026,8,10]],"date-time":"2026-08-10T00:00:00Z","timestamp":1786320000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,8,10]],"date-time":"2026-08-10T00:00:00Z","timestamp":1786320000000},"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":["J Supercomput"],"DOI":"10.1007\/s11227-026-08739-4","type":"journal-article","created":{"date-parts":[[2026,8,10]],"date-time":"2026-08-10T02:41:33Z","timestamp":1786329693000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["OAHR: occlusion-aware hypergraph reasoning dual-stream network for noisy skeleton-based action recognition"],"prefix":"10.1007","volume":"82","author":[{"given":"Xinyi","family":"Su","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongwei","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xia","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,8,10]]},"reference":[{"key":"8739_CR1","doi-asserted-by":"publisher","first-page":"5784","DOI":"10.1109\/TMM.2025.3543034","volume":"27","author":"H Xu","year":"2025","unstructured":"Xu H, Gao Y, Hui Z et al (2025) Language knowledge-assisted representation learning for skeleton-based action recognition. IEEE Trans Multimed 27:5784\u20135799","journal-title":"IEEE Trans Multimed"},{"key":"8739_CR2","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2025.113757","volume":"323","author":"C Xu","year":"2025","unstructured":"Xu C, Yun X, Sun Y et al (2025) Heterogeneous modal collaborative training network for human action recognition. Knowl Based Syst 323:113757","journal-title":"Knowl Based Syst"},{"key":"8739_CR3","doi-asserted-by":"publisher","first-page":"1242","DOI":"10.1109\/TMM.2024.3521749","volume":"27","author":"S Liu","year":"2025","unstructured":"Liu S, Wang X, Xiong R et al (2025) Gcn-based multi-modality fusion network for action recognition. IEEE Trans Multimed 27:1242\u20131253","journal-title":"IEEE Trans Multimed"},{"key":"8739_CR4","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2024.111106","volume":"159","author":"Z Wu","year":"2025","unstructured":"Wu Z, Ding Y, Wan L et al (2025) Local and global self-attention enhanced graph convolutional network for skeleton-based action recognition. Pattern Recogn 159:111106","journal-title":"Pattern Recogn"},{"issue":"7","key":"8739_CR5","doi-asserted-by":"publisher","first-page":"5149","DOI":"10.1109\/TPAMI.2024.3363831","volume":"46","author":"S Yang","year":"2024","unstructured":"Yang S, Liu J, Lu S et al (2024) One-shot action recognition via multi-scale spatial-temporal skeleton matching. IEEE Trans Pattern Anal Mach Intell 46(7):5149\u20135156","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"12","key":"8739_CR6","doi-asserted-by":"publisher","first-page":"20064","DOI":"10.1109\/JSEN.2024.3388154","volume":"24","author":"M Zhang","year":"2024","unstructured":"Zhang M, Quan Z, Wang W et al (2024) Asmgcn: attention-based semantic-guided multistream graph convolution network for skeleton action recognition. IEEE Sens J 24(12):20064\u201320075","journal-title":"IEEE Sens J"},{"key":"8739_CR7","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TIP.2023.3334954","volume":"33","author":"X Wang","year":"2024","unstructured":"Wang X, Zhang W, Wang C et al (2024) Dynamic dense graph convolutional network for skeleton-based human motion prediction. IEEE Trans Image Process 33:1\u201315","journal-title":"IEEE Trans Image Process"},{"issue":"1","key":"8739_CR8","doi-asserted-by":"publisher","first-page":"202","DOI":"10.1109\/TETC.2022.3230912","volume":"12","author":"B Filtjens","year":"2024","unstructured":"Filtjens B, Vanrumste B, Slaets P (2024) Skeleton-based action segmentation with multi-stage spatial-temporal graph convolutional neural networks. IEEE Trans Emerg Top Comput 12(1):202\u2013212","journal-title":"IEEE Trans Emerg Top Comput"},{"key":"8739_CR9","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2024.110948","volume":"157","author":"W Liu","year":"2025","unstructured":"Liu W, Jia X, Zhong X et al (2025) Dynamic and static mutual fitting for action recognition. Pattern Recogn 157:110948","journal-title":"Pattern Recogn"},{"key":"8739_CR10","doi-asserted-by":"publisher","DOI":"10.1016\/j.cviu.2024.104059","volume":"246","author":"Z Niu","year":"2024","unstructured":"Niu Z, Lu K, Xue J et al (2024) Skeleton cluster tracking for robust multi-view multi-person 3d human pose estimation. Comput Vis Image Underst 246:104059","journal-title":"Comput Vis Image Underst"},{"key":"8739_CR11","doi-asserted-by":"crossref","unstructured":"Li S, He X, Song W (2023) Graph diffusion convolutional network for skeleton based semantic recognition of two-person actions. IEEE Trans Pattern Anal Mach Intell 1\u201317","DOI":"10.1109\/TPAMI.2023.3238411"},{"key":"8739_CR12","doi-asserted-by":"crossref","unstructured":"Hong S, Kim C, Yoon S (2025) Salad: Skeleton-aware latent diffusion for text-driven motion generation and editing. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. pp 7158\u20137168","DOI":"10.1109\/CVPR52734.2025.00671"},{"key":"8739_CR13","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2025.112855","volume":"172","author":"H Yang","year":"2025","unstructured":"Yang H, Wang S, Jiang L et al (2025) Hierarchical adaptive multi-scale hypergraph attention convolution network for skeleton-based action recognition. Appl Soft Comput 172:112855","journal-title":"Appl Soft Comput"},{"key":"8739_CR14","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2024.110536","volume":"153","author":"Y Li","year":"2024","unstructured":"Li Y, Wei G, Desrosiers C et al (2024) Decoupled and boosted learning for skeleton-based dynamic hand gesture recognition. Pattern Recogn 153:110536","journal-title":"Pattern Recogn"},{"key":"8739_CR15","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2025.111923","volume":"169","author":"Y Yang","year":"2026","unstructured":"Yang Y, Liang G, Wang C et al (2026) Trunk-branch contrastive network with multi-view deformable aggregation for multi-view action recognition. Pattern Recogn 169:111923","journal-title":"Pattern Recogn"},{"key":"8739_CR16","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2025.126646","volume":"272","author":"L Zhou","year":"2025","unstructured":"Zhou L, Jiao X (2025) Multi-modal and multi-part with skeletons and texts for action recognition. Expert Syst Appl 272:126646","journal-title":"Expert Syst Appl"},{"key":"8739_CR17","doi-asserted-by":"publisher","first-page":"2477","DOI":"10.1109\/TIP.2024.3378886","volume":"33","author":"W Myung","year":"2024","unstructured":"Myung W, Su N, Xue J-H et al (2024) Degcn: deformable graph convolutional networks for skeleton-based action recognition. IEEE Trans Image Process 33:2477\u20132490","journal-title":"IEEE Trans Image Process"},{"key":"8739_CR18","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2024.110262","volume":"150","author":"X Yin","year":"2024","unstructured":"Yin X, Zhong J, Lian D et al (2024) Spatiotemporal progressive inward-outward aggregation network for skeleton-based action recognition. Pattern Recogn 150:110262","journal-title":"Pattern Recogn"},{"key":"8739_CR19","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2025.113045","volume":"311","author":"U Kilic","year":"2025","unstructured":"Kilic U, Karadag O, Ozyer G (2025) Agms-gcn: attention-guided multi-scale graph convolutional networks for skeleton-based action recognition. Knowl Based Syst 311:113045","journal-title":"Knowl Based Syst"},{"key":"8739_CR20","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2023.120683","volume":"232","author":"L Hu","year":"2023","unstructured":"Hu L, Liu S, Feng W (2023) Skeleton-based action recognition with local dynamic spatial\u2013temporal aggregation. Expert Syst Appl 232:120683","journal-title":"Expert Syst Appl"},{"key":"8739_CR21","doi-asserted-by":"publisher","first-page":"56","DOI":"10.1109\/TMM.2024.3521774","volume":"27","author":"Q Miao","year":"2025","unstructured":"Miao Q, Xin W, Liu R et al (2025) Adaptive pitfall: exploring the effectiveness of adaptation in skeleton-based action recognition. IEEE Trans Multimed 27:56\u201371","journal-title":"IEEE Trans Multimed"},{"key":"8739_CR22","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2025.112797","volume":"171","author":"K Wu","year":"2025","unstructured":"Wu K, Peng B, Zhai D (2025) Leveraging uncertainty-guided spatial\u2013temporal mutuality for skeleton-based action recognition. Appl Soft Comput 171:112797","journal-title":"Appl Soft Comput"},{"key":"8739_CR23","doi-asserted-by":"publisher","first-page":"652","DOI":"10.1016\/j.aej.2025.05.069","volume":"128","author":"Y Zhu","year":"2025","unstructured":"Zhu Y, Yu W, Li R (2025) Sagcn: a spatiotemporal attention-weighted graph convolutional network with iot integration for adolescent tennis motion analysis. Alex Eng J 128:652\u2013662","journal-title":"Alex Eng J"},{"issue":"4","key":"8739_CR24","doi-asserted-by":"publisher","first-page":"7615","DOI":"10.1109\/TNNLS.2024.3384770","volume":"36","author":"S-L Liu","year":"2025","unstructured":"Liu S-L, Ding Y-N, Zhang J-R et al (2025) Multidimensional refinement graph convolutional network with robust decouple loss for fine-grained skeleton-based action recognition. IEEE Trans Neural Netw Learn Syst 36(4):7615\u20137626","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"8739_CR25","doi-asserted-by":"crossref","unstructured":"Duan H, Zhao Y, Chen K (2022) Revisiting skeleton-based action recognition. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. pp 2969\u20132978","DOI":"10.1109\/CVPR52688.2022.00298"},{"key":"8739_CR26","doi-asserted-by":"crossref","unstructured":"Chen Y, Guo J, Guo S, Tao D (2025) Neuron: Learning context-aware evolving representations for zero-shot skeleton action recognition. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 8721\u20138730","DOI":"10.1109\/CVPR52734.2025.00815"},{"key":"8739_CR27","first-page":"525","volume":"37","author":"J Dong","year":"2023","unstructured":"Dong J, Sun S, Liu Z et al (2023) Hierarchical contrast for unsupervised skeleton-based action representation learning. Proc AAAI Conf Artif Intell 37:525\u2013533","journal-title":"Proc AAAI Conf Artif Intell"},{"issue":"9","key":"8739_CR28","doi-asserted-by":"publisher","first-page":"12130","DOI":"10.1109\/TNNLS.2023.3252172","volume":"35","author":"X Gao","year":"2024","unstructured":"Gao X, Yang Y, Wu Y et al (2024) Learning heterogeneous spatial\u2013temporal context for skeleton-based action recognition. IEEE Trans Neural Netw Learn Syst 35(9):12130\u201312141","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"8739_CR29","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2025.114391","volume":"187","author":"Z Tian","year":"2026","unstructured":"Tian Z, Zhao F, Liu H et al (2026) Hdmfnet: learning complementary spatiotemporal representations via heterogeneous dual-branch multimodal fusion network for human action recognition. Appl Soft Comput 187:114391","journal-title":"Appl Soft Comput"},{"issue":"3","key":"8739_CR30","doi-asserted-by":"publisher","first-page":"2101","DOI":"10.1109\/TCSVT.2024.3491133","volume":"35","author":"T Zhuang","year":"2025","unstructured":"Zhuang T, Qin Z, Ding Y et al (2025) Dsdc-gcn: decoupled static-dynamic co-occurrence graph convolutional networks for skeleton-based action recognition. IEEE Trans Circuits Syst Video Technol 35(3):2101\u20132117","journal-title":"IEEE Trans Circuits Syst Video Technol"},{"key":"8739_CR31","first-page":"8332","volume":"39","author":"W Weng","year":"2025","unstructured":"Weng W, Wang H, Wang J, He L, Xie G-S (2025) Usdrl: unified skeleton-based dense representation learning with multi-grained feature decorrelation. Proc AAAI Conf Artif Intell 39:8332\u20138340","journal-title":"Proc AAAI Conf Artif Intell"},{"issue":"1","key":"8739_CR32","doi-asserted-by":"publisher","first-page":"514","DOI":"10.1109\/TPAMI.2024.3466212","volume":"47","author":"S Chi","year":"2025","unstructured":"Chi S, Chi H-G, Huang Q et al (2025) Infogcn++: learning representation by predicting the future for online skeleton-based action recognition. IEEE Trans Pattern Anal Mach Intell 47(1):514\u2013528","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"8739_CR33","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2025.112125","volume":"171","author":"N Ma","year":"2026","unstructured":"Ma N, Xu G, Han Y et al (2026) Thtformer: topology-adaptive hypergraph transformer network for skeleton-based action recognition. Pattern Recogn 171:112125","journal-title":"Pattern Recogn"},{"key":"8739_CR34","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2023.109528","volume":"140","author":"L Hedegaard","year":"2023","unstructured":"Hedegaard L, Heidari N, Iosifidis A (2023) Continual spatio-temporal graph convolutional networks. Pattern Recogn 140:109528","journal-title":"Pattern Recogn"},{"key":"8739_CR35","doi-asserted-by":"publisher","first-page":"3207","DOI":"10.1109\/TMM.2023.3307933","volume":"26","author":"M Wang","year":"2024","unstructured":"Wang M, Li X, Chen S et al (2024) Learning representations by contrastive spatiotemporal clustering for skeleton-based action recognition. IEEE Trans Multimed 26:3207\u20133220","journal-title":"IEEE Trans Multimed"},{"key":"8739_CR36","first-page":"5949","volume":"38","author":"C Wu","year":"2024","unstructured":"Wu C, Wu X-J, Kittler J et al (2024) Scd-net: spatiotemporal clues disentanglement network for self-supervised skeleton-based action recognition. Proc AAAI Conf Artif Intell 38:5949\u20135957","journal-title":"Proc AAAI Conf Artif Intell"},{"issue":"1","key":"8739_CR37","doi-asserted-by":"publisher","first-page":"274","DOI":"10.1109\/TCSVT.2023.3284493","volume":"34","author":"Z Jin","year":"2024","unstructured":"Jin Z, Wang Y, Wang Q et al (2024) Ssrl: self-supervised spatial-temporal representation learning for 3d action recognition. IEEE Trans Circuits Syst Video Technol 34(1):274\u2013285","journal-title":"IEEE Trans Circuits Syst Video Technol"},{"key":"8739_CR38","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2025.111377","volume":"162","author":"R Liu","year":"2025","unstructured":"Liu R, Liu Y, Wu M et al (2025) Sg-clr: semantic representation-guided contrastive learning for self-supervised skeleton-based action recognition. Pattern Recogn 162:111377","journal-title":"Pattern Recogn"},{"key":"8739_CR39","doi-asserted-by":"crossref","unstructured":"Wang H, Ma X, Kuang J, GJ (2025) Heterogeneous skeleton-based action representation learning. In: Proceedings of the Computer Vision and Pattern Recognition Conference. pp 19154\u201319164","DOI":"10.1109\/CVPR52734.2025.01784"},{"key":"8739_CR40","doi-asserted-by":"publisher","first-page":"3437","DOI":"10.1109\/TMM.2025.3535284","volume":"27","author":"M Ghaseb","year":"2025","unstructured":"Ghaseb M, Elhayek A, Alsolami F et al (2025) S3gaar: segmented spatiotemporal skeleton graph-attention for action recognition. IEEE Trans Multimed 27:3437\u20133446","journal-title":"IEEE Trans Multimed"},{"key":"8739_CR41","doi-asserted-by":"publisher","first-page":"7585","DOI":"10.1109\/TIP.2025.3632229","volume":"34","author":"Y Yang","year":"2025","unstructured":"Yang Y, Zhang J, Zhang J et al (2025) Expressive keypoints for skeleton-based action recognition via progressive skeleton evolution. IEEE Trans Image Process 34:7585\u20137599","journal-title":"IEEE Trans Image Process"},{"key":"8739_CR42","doi-asserted-by":"crossref","unstructured":"Chang H, Ren P, Zhang H (2025) Hierarchical-aware orthogonal disentanglement framework for fine-grained skeleton-based action recognition. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision. pp 11252\u201311261","DOI":"10.1109\/ICCV51701.2025.01047"},{"key":"8739_CR43","doi-asserted-by":"crossref","unstructured":"Zhou Y, Xu T, Wu C (2025) Adaptive hyper-graph convolution network for skeleton-based human action recognition with virtual connections. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision. pp 12648\u201312658","DOI":"10.1109\/ICCV51701.2025.01175"},{"key":"8739_CR44","doi-asserted-by":"crossref","unstructured":"Liu H, Liu Y, Ren M, et\u00a0al. (2025) Revealing key details to see differences: A novel prototypical perspective for skeleton-based action recognition. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 29248\u201329257","DOI":"10.1109\/CVPR52734.2025.02723"},{"key":"8739_CR45","first-page":"6917","volume":"38","author":"X Yun","year":"2024","unstructured":"Yun X, Xu C, Riou K et al (2024) Behavioral recognition of skeletal data based on targeted dual fusion strategy. Proc AAAI Conf Artif Intell 38:6917\u20136925","journal-title":"Proc AAAI Conf Artif Intell"},{"key":"8739_CR46","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2025.114948","volume":"333","author":"M Hu","year":"2026","unstructured":"Hu M, Wang L, Yao C et al (2026) Representation learning for skeleton-based action recognition from a causal perspective. Knowl Based Syst 333:114948","journal-title":"Knowl Based Syst"}],"container-title":["The Journal of Supercomputing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-026-08739-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11227-026-08739-4","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-026-08739-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,10]],"date-time":"2026-08-10T02:41:36Z","timestamp":1786329696000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11227-026-08739-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8,10]]},"references-count":46,"journal-issue":{"issue":"12","published-online":{"date-parts":[[2026,8]]}},"alternative-id":["8739"],"URL":"https:\/\/doi.org\/10.1007\/s11227-026-08739-4","relation":{},"ISSN":["1573-0484"],"issn-type":[{"value":"1573-0484","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,8,10]]},"assertion":[{"value":"31 January 2026","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"25 July 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 August 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors declare no financial or personal conflict of interest.","order":1,"name":"Ethics","label":"Conflict of interest","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"This study does not involve human or animal subjects. Ethical approval and informed consent are not applicable.","order":2,"name":"Ethics","label":"Ethics approval and consent to participate","group":{"name":"EthicsHeading","label":"Declarations"}}],"article-number":"614"}}