{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T03:25:26Z","timestamp":1782789926910,"version":"3.54.5"},"reference-count":54,"publisher":"Springer Science and Business Media LLC","issue":"12","license":[{"start":{"date-parts":[[2023,6,21]],"date-time":"2023-06-21T00:00:00Z","timestamp":1687305600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,6,21]],"date-time":"2023-06-21T00:00:00Z","timestamp":1687305600000},"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":["Int. J. Mach. Learn. &amp; Cyber."],"published-print":{"date-parts":[[2023,12]]},"DOI":"10.1007\/s13042-023-01879-6","type":"journal-article","created":{"date-parts":[[2023,6,21]],"date-time":"2023-06-21T04:19:19Z","timestamp":1687321159000},"page":"4029-4045","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["QMGR-Net: quaternion multi-graph reasoning network for 3D hand pose estimation"],"prefix":"10.1007","volume":"14","author":[{"given":"Haomin","family":"Ni","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shengli","family":"Xie","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pingping","family":"Xu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaozhao","family":"Fang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2342-4434","authenticated-orcid":false,"given":"Weijun","family":"Sun","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ribo","family":"Fang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2023,6,21]]},"reference":[{"issue":"3","key":"1879_CR1","doi-asserted-by":"publisher","first-page":"355","DOI":"10.1109\/TVCG.2008.190","volume":"15","author":"T Lee","year":"2009","unstructured":"Lee T, Hollerer T (2009) Multithreaded hybrid feature tracking for markerless augmented reality. IEEE Trans Visual Computer Graph 15(3):355\u2013368","journal-title":"IEEE Trans Visual Computer Graph"},{"issue":"4","key":"1879_CR2","doi-asserted-by":"publisher","first-page":"501","DOI":"10.1109\/TVCG.2015.2391860","volume":"21","author":"Y Jang","year":"2015","unstructured":"Jang Y, Noh S-T, Chang HJ, Kim T-K, Woo W (2015) 3D finger cape: clicking action and position estimation under self-occlusions in egocentric viewpoint. IEEE Trans Visual Computer Graph 21(4):501\u2013510","journal-title":"IEEE Trans Visual Computer Graph"},{"key":"1879_CR3","unstructured":"Simonyan K, Zisserman A (2014) Two-stream convolutional networks for action recognition in videos. Adv Neural Inform Process Syst 27"},{"key":"1879_CR4","doi-asserted-by":"crossref","unstructured":"Shi L, Zhang Y, Cheng J, Lu H (2019) Two-stream adaptive graph convolutional networks for skeleton-based action recognition. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 12026\u201312035","DOI":"10.1109\/CVPR.2019.01230"},{"issue":"5","key":"1879_CR5","doi-asserted-by":"publisher","first-page":"1391","DOI":"10.1109\/TMM.2014.2317311","volume":"16","author":"DS Alexiadis","year":"2014","unstructured":"Alexiadis DS, Daras P (2014) Quaternionic signal processing techniques for automatic evaluation of dance performances from mocap data. IEEE Trans Multimedia 16(5):1391\u20131406","journal-title":"IEEE Trans Multimedia"},{"issue":"3","key":"1879_CR6","doi-asserted-by":"publisher","first-page":"1007","DOI":"10.3390\/s21031007","volume":"21","author":"C Xu","year":"2021","unstructured":"Xu C, Jiang Y, Zhou J, Liu Y (2021) Semi-supervised joint learning for hand gesture recognition from a single color image. Sensors 21(3):1007","journal-title":"Sensors"},{"issue":"3","key":"1879_CR7","doi-asserted-by":"publisher","first-page":"42","DOI":"10.3390\/electronics5030042","volume":"5","author":"M Bianchi","year":"2016","unstructured":"Bianchi M, Haschke R, B\u00fcscher G, Ciotti S, Carbonaro N, Tognetti A (2016) A multi-modal sensing glove for human manual-interaction studies. Electronics 5(3):42","journal-title":"Electronics"},{"key":"1879_CR8","doi-asserted-by":"crossref","unstructured":"Chossat J-B, Tao Y, Duchaine V, Park Y-L (2015) Wearable soft artificial skin for hand motion detection with embedded microfluidic strain sensing 2568\u20132573","DOI":"10.1109\/ICRA.2015.7139544"},{"key":"1879_CR9","doi-asserted-by":"publisher","first-page":"2977","DOI":"10.1109\/TIP.2019.2955280","volume":"29","author":"Y Wang","year":"2019","unstructured":"Wang Y, Zhang B, Peng C (2019) Srhandnet: Real-time 2d hand pose estimation with simultaneous region localization. IEEE Tans Image Process 29:2977\u20132986","journal-title":"IEEE Tans Image Process"},{"key":"1879_CR10","doi-asserted-by":"crossref","unstructured":"Chen Y, Ma H, Kong D, Yan X, Wu J, Fan W, Xie X (2020) Nonparametric structure regularization machine for 2d hand pose estimation. In: Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision, pp. 381\u2013390","DOI":"10.1109\/WACV45572.2020.9093271"},{"key":"1879_CR11","doi-asserted-by":"crossref","unstructured":"Sharp T, Keskin C, Robertson D, Taylor J, Shotton J, Kim D, Rhemann C, Leichter I, Vinnikov A, Wei Y, et\u00a0al. (2015) Accurate, robust, and flexible real-time hand tracking. In: Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, pp. 3633\u20133642","DOI":"10.1145\/2702123.2702179"},{"key":"1879_CR12","doi-asserted-by":"crossref","unstructured":"Sridhar S, Mueller F, Oulasvirta A, Theobalt C (2015) Fast and robust hand tracking using detection-guided optimization. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3213\u20133221","DOI":"10.1109\/CVPR.2015.7298941"},{"key":"1879_CR13","doi-asserted-by":"crossref","unstructured":"Tan DJ, Cashman T, Taylor J, Fitzgibbon A, Tarlow D, Khamis S, Izadi S, Shotton J (2016) Fits like a glove: Rapid and reliable hand shape personalization. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 5610\u20135619","DOI":"10.1109\/CVPR.2016.605"},{"issue":"2","key":"1879_CR14","doi-asserted-by":"publisher","first-page":"172","DOI":"10.1007\/s11263-016-0895-4","volume":"118","author":"D Tzionas","year":"2016","unstructured":"Tzionas D, Ballan L, Srikantha A, Aponte P, Pollefeys M, Gall J (2016) Capturing hands in action using discriminative salient points and physics simulation. Int J Comput Vis 118(2):172\u2013193","journal-title":"Int J Comput Vis"},{"issue":"1","key":"1879_CR15","doi-asserted-by":"publisher","first-page":"157","DOI":"10.1007\/s10044-021-01048-x","volume":"25","author":"X Guo","year":"2022","unstructured":"Guo X, Xu S, Lin X, Sun Y, Ma X (2022) 3D hand pose estimation from a single rgb image through semantic decomposition of vae latent space. Pattern Anal Appl 25(1):157\u2013167","journal-title":"Pattern Anal Appl"},{"key":"1879_CR16","doi-asserted-by":"crossref","unstructured":"Zimmermann C, Brox T (2017) Learning to estimate 3d hand pose from single rgb images. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 4903\u20134911","DOI":"10.1109\/ICCV.2017.525"},{"key":"1879_CR17","doi-asserted-by":"crossref","unstructured":"Oberweger M, Lepetit V (2017) Deepprior++: Improving fast and accurate 3d hand pose estimation. In: Proceedings of the IEEE International Conference on Computer Vision Workshops, pp. 585\u2013594","DOI":"10.1109\/ICCVW.2017.75"},{"key":"1879_CR18","unstructured":"Oberweger M, Wohlhart P, Lepetit V (2015) Hands deep in deep learning for hand pose estimation. arXiv preprint arXiv:1502.06807"},{"key":"1879_CR19","doi-asserted-by":"crossref","unstructured":"Moon G, Chang JY, Lee KM (2018) V2v-posenet: Voxel-to-voxel prediction network for accurate 3d hand and human pose estimation from a single depth map. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 5079\u20135088","DOI":"10.1109\/CVPR.2018.00533"},{"key":"1879_CR20","doi-asserted-by":"crossref","unstructured":"Moon G, Yu S-I, Wen H, Shiratori T, Lee KM (2020) Interhand2. 6m: A dataset and baseline for 3d interacting hand pose estimation from a single rgb image. In: European Conference on Computer Vision, pp. 548\u2013564. Springer","DOI":"10.1007\/978-3-030-58565-5_33"},{"key":"1879_CR21","doi-asserted-by":"publisher","first-page":"138","DOI":"10.1016\/j.neucom.2018.06.097","volume":"395","author":"X Chen","year":"2020","unstructured":"Chen X, Wang G, Guo H, Zhang C (2020) Pose guided structured region ensemble network for cascaded hand pose estimation. Neurocomputing 395:138\u2013149","journal-title":"Neurocomputing"},{"issue":"4","key":"1879_CR22","doi-asserted-by":"publisher","first-page":"956","DOI":"10.1109\/TPAMI.2018.2827052","volume":"41","author":"L Ge","year":"2018","unstructured":"Ge L, Liang H, Yuan J, Thalmann D (2018) Real-time 3d hand pose estimation with 3d convolutional neural networks. IEEE Trans Pattern Anal Mach Intellig 41(4):956\u2013970","journal-title":"IEEE Trans Pattern Anal Mach Intellig"},{"key":"1879_CR23","doi-asserted-by":"crossref","unstructured":"Liao M, Zhu Z, Shi B, Xia G-s, Bai X (2018) Rotation-sensitive regression for oriented scene text detection. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 5909\u20135918","DOI":"10.1109\/CVPR.2018.00619"},{"key":"1879_CR24","doi-asserted-by":"crossref","unstructured":"Mueller F, Bernard F, Sotnychenko O, Mehta D, Sridhar S, Casas D, Theobalt C (2018) Ganerated hands for real-time 3d hand tracking from monocular rgb. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 49\u201359","DOI":"10.1109\/CVPR.2018.00013"},{"key":"1879_CR25","doi-asserted-by":"crossref","unstructured":"Spurr A, Song J, Park S, Hilliges O (2018) Cross-modal deep variational hand pose estimation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 89\u201398","DOI":"10.1109\/CVPR.2018.00017"},{"key":"1879_CR26","doi-asserted-by":"crossref","unstructured":"Yang L, Yao A (2019) Disentangling latent hands for image synthesis and pose estimation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 9877\u20139886","DOI":"10.1109\/CVPR.2019.01011"},{"key":"1879_CR27","doi-asserted-by":"crossref","unstructured":"Khaleghi L, Sepas-Moghaddam A, Marshall J, Etemad A (2022) Multi-view video-based 3d hand pose estimation. IEEE Trans Artif Intellig","DOI":"10.1109\/TAI.2022.3195968"},{"key":"1879_CR28","unstructured":"Zhang J, Jiao J, Chen M, Qu L, Xu X, Yang Q (2016) 3D hand pose tracking and estimation using stereo matching. arXiv preprint arXiv:1610.07214"},{"key":"1879_CR29","doi-asserted-by":"crossref","unstructured":"Panteleris P, Argyros A (2017) Back to rgb: 3D tracking of hands and hand-object interactions based on short-baseline stereo. In: Proceedings of the IEEE International Conference on Computer Vision Workshops, pp. 575\u2013584","DOI":"10.1109\/ICCVW.2017.74"},{"key":"1879_CR30","unstructured":"Arjovsky M, Shah A, Bengio Y (2016) Unitary evolution recurrent neural networks. In: International Conference on Machine Learning, pp. 1120\u20131128. PMLR"},{"key":"1879_CR31","unstructured":"Guberman N (2016) On complex valued convolutional neural networks. arXiv preprint arXiv:1602.09046"},{"key":"1879_CR32","unstructured":"Trabelsi C, Bilaniuk O, Serdyuk D, Subramanian S, Santos JF, Mehri S, Rostamzadeh N, Bengio Y, Pal CJ (2017) Deep complex networks. CoRR abs\/1705.09792arXiv:1705.09792"},{"key":"1879_CR33","doi-asserted-by":"crossref","unstructured":"Shen W, Zhang B, Huang S, Wei Z, Zhang Q (2020) 3d-rotation-equivariant quaternion neural networks. In: European Conference on Computer Vision, pp. 531\u2013547. Springer","DOI":"10.1007\/978-3-030-58565-5_32"},{"key":"1879_CR34","doi-asserted-by":"crossref","unstructured":"Parcollet T, Morchid M, Linar\u00e8s G (2019) Quaternion convolutional neural networks for heterogeneous image processing. In: ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 8514\u20138518","DOI":"10.1109\/ICASSP.2019.8682495"},{"key":"1879_CR35","doi-asserted-by":"crossref","unstructured":"Grassucci E, Cicero E, Comminiello D (2021) Quaternion generative adversarial networks. arXiv preprint arXiv:2104.09630","DOI":"10.1007\/978-3-030-91390-8_4"},{"key":"1879_CR36","unstructured":"Defferrard M, Bresson X, Vandergheynst P (2016) Convolutional neural networks on graphs with fast localized spectral filtering. Adv Neur Inform Process Syst 29"},{"key":"1879_CR37","unstructured":"Kipf TN, Welling M (2016) Semi-supervised classification with graph convolutional networks. arXiv preprint arXiv:1609.02907"},{"key":"1879_CR38","doi-asserted-by":"crossref","unstructured":"Li M, Chen S, Chen X, Zhang Y, Wang Y, Tian Q (2019) Actional-structural graph convolutional networks for skeleton-based action recognition. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 3595\u20133603","DOI":"10.1109\/CVPR.2019.00371"},{"key":"1879_CR39","doi-asserted-by":"publisher","first-page":"57","DOI":"10.1016\/j.neucom.2022.03.040","volume":"491","author":"Y Xu","year":"2022","unstructured":"Xu Y, Mu L, Ji Z, Liu X, Han J (2022) Meta hyperbolic networks for zero-shot learning. Neurocomputing 491:57\u201366","journal-title":"Neurocomputing"},{"key":"1879_CR40","doi-asserted-by":"crossref","unstructured":"Fang L, Liu X, Liu L, Xu H, Kang W (2020) Jgr-p2o: Joint graph reasoning based pixel-to-offset prediction network for 3d hand pose estimation from a single depth image. In: European Conference on Computer Vision, pp. 120\u2013137. Springer","DOI":"10.1007\/978-3-030-58539-6_8"},{"key":"1879_CR41","unstructured":"Kipf TN, Welling M (2016) Semi-supervised classification with graph convolutional networks. arXiv preprint arXiv:1609.02907"},{"key":"1879_CR42","doi-asserted-by":"crossref","unstructured":"Hamilton WR (1848) Xi. on quaternions; or on a new system of imaginaries in algebra. The London, Edinburgh, and Dublin Philosophical Magazine and Journal of Science 33(219), 58\u201360","DOI":"10.1080\/14786444808646046"},{"key":"1879_CR43","doi-asserted-by":"crossref","unstructured":"Gaudet CJ, Maida AS (2018) Deep quaternion networks. In: 2018 International Joint Conference on Neural Networks (IJCNN), pp. 1\u20138. IEEE","DOI":"10.1109\/IJCNN.2018.8489651"},{"key":"1879_CR44","unstructured":"Krizhevsky A, Sutskever I, Hinton GE (2012) Imagenet classification with deep convolutional neural networks. Adv Neur Inform Process Syst 25"},{"key":"1879_CR45","doi-asserted-by":"crossref","unstructured":"He K, Zhang X, Ren S, Sun J (2016) Deep residual learning for image recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 770\u2013778","DOI":"10.1109\/CVPR.2016.90"},{"key":"1879_CR46","doi-asserted-by":"crossref","unstructured":"Moon G, Chang JY, Lee KM (2019) Camera distance-aware top-down approach for 3d multi-person pose estimation from a single rgb image. In: Proceedings of the IEEE\/cvf International Conference on Computer Vision, pp. 10133\u201310142","DOI":"10.1109\/ICCV.2019.01023"},{"key":"1879_CR47","doi-asserted-by":"crossref","unstructured":"Moon G, Chang JY, Lee KM (2018) V2v-posenet: Voxel-to-voxel prediction network for accurate 3d hand and human pose estimation from a single depth map. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 5079\u20135088","DOI":"10.1109\/CVPR.2018.00533"},{"key":"1879_CR48","doi-asserted-by":"crossref","unstructured":"Oikonomidis I, Kyriazis N, Argyros AA (2011) Efficient model-based 3d tracking of hand articulations using kinect. In: BmVC, vol. 1, p. 3","DOI":"10.5244\/C.25.101"},{"key":"1879_CR49","doi-asserted-by":"crossref","unstructured":"Qian C, Sun X, Wei Y, Tang X, Sun J (2014) Realtime and robust hand tracking from depth. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1106\u20131113","DOI":"10.1109\/CVPR.2014.145"},{"key":"1879_CR50","unstructured":"Chen L, Lin S-Y, Xie Y, Tang H, Xue Y, Xie X, Lin Y-Y, Fan W (2018) Generating realistic training images based on tonality-alignment generative adversarial networks for hand pose estimation. arXiv preprint arXiv:1811.09916"},{"key":"1879_CR51","doi-asserted-by":"crossref","unstructured":"Zhou Y, Habermann M, Xu W, Habibie I, Theobalt C, Xu F (2020) Monocular real-time hand shape and motion capture using multi-modal data. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 5346\u20135355","DOI":"10.1109\/CVPR42600.2020.00539"},{"key":"1879_CR52","doi-asserted-by":"crossref","unstructured":"Zhao L, Peng X, Chen Y, Kapadia M, Metaxas DN (2020) Knowledge as priors: Cross-modal knowledge generalization for datasets without superior knowledge. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 6528\u20136537","DOI":"10.1109\/CVPR42600.2020.00656"},{"key":"1879_CR53","doi-asserted-by":"crossref","unstructured":"Doosti B, Naha S, Mirbagheri M, Crandall DJ (2020) Hope-net: A graph-based model for hand-object pose estimation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 6608\u20136617","DOI":"10.1109\/CVPR42600.2020.00664"},{"issue":"20","key":"1879_CR54","doi-asserted-by":"publisher","first-page":"6747","DOI":"10.3390\/s21206747","volume":"21","author":"Y Liu","year":"2021","unstructured":"Liu Y, Jiang J, Sun J, Wang X (2021) Internet+: A light network for hand pose estimation. Sensors 21(20):6747","journal-title":"Sensors"}],"container-title":["International Journal of Machine Learning and Cybernetics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-023-01879-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s13042-023-01879-6\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-023-01879-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,10,13]],"date-time":"2023-10-13T05:23:27Z","timestamp":1697174607000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s13042-023-01879-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,6,21]]},"references-count":54,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2023,12]]}},"alternative-id":["1879"],"URL":"https:\/\/doi.org\/10.1007\/s13042-023-01879-6","relation":{},"ISSN":["1868-8071","1868-808X"],"issn-type":[{"value":"1868-8071","type":"print"},{"value":"1868-808X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,6,21]]},"assertion":[{"value":"25 July 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"23 May 2023","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 June 2023","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}