{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T03:20:44Z","timestamp":1740108044407,"version":"3.37.3"},"reference-count":47,"publisher":"Springer Science and Business Media LLC","issue":"28","license":[{"start":{"date-parts":[[2023,7,31]],"date-time":"2023-07-31T00:00:00Z","timestamp":1690761600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,7,31]],"date-time":"2023-07-31T00:00:00Z","timestamp":1690761600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["No.61873046"],"award-info":[{"award-number":["No.61873046"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["No.U1708263"],"award-info":[{"award-number":["No.U1708263"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput &amp; Applic"],"published-print":{"date-parts":[[2023,10]]},"DOI":"10.1007\/s00521-023-08884-4","type":"journal-article","created":{"date-parts":[[2023,7,31]],"date-time":"2023-07-31T13:02:19Z","timestamp":1690808539000},"page":"21043-21054","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["HRI: human reasoning inspired hand pose estimation with shape memory update and contact-guided refinement"],"prefix":"10.1007","volume":"35","author":[{"given":"Xuefeng","family":"Li","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7232-9479","authenticated-orcid":false,"given":"Xiangbo","family":"Lin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,7,31]]},"reference":[{"key":"8884_CR1","doi-asserted-by":"publisher","first-page":"35","DOI":"10.1016\/j.imavis.2019.06.003","volume":"89","author":"A Ahmad","year":"2019","unstructured":"Ahmad A, Migniot C, Dipanda A (2019) Hand pose estimation and tracking in real and virtual interaction: a review. Image Vision Comput 89:35\u201349","journal-title":"Image Vision Comput"},{"key":"8884_CR2","doi-asserted-by":"crossref","unstructured":"Baek S, Kim KI, Kim TK (2020) Weakly-supervised domain adaptation via gan and mesh model for estimating 3d hand poses interacting objects. In: CVPR, pp 6121\u20136131","DOI":"10.1109\/CVPR42600.2020.00616"},{"key":"8884_CR3","doi-asserted-by":"crossref","unstructured":"Chao YW, Yang W, Xiang Y, et\u00a0al (2021) Dexycb: A benchmark for capturing hand grasping of objects. In: CVPR, pp 9044\u20139053","DOI":"10.1109\/CVPR46437.2021.00893"},{"key":"8884_CR4","doi-asserted-by":"crossref","unstructured":"Chen L, Lin SY, Xie Y, et\u00a0al (2021) Temporal-aware self-supervised learning for 3d hand pose and mesh estimation in videos. In: WACV, pp 1050\u20131059","DOI":"10.1109\/WACV48630.2021.00109"},{"key":"8884_CR5","doi-asserted-by":"crossref","unstructured":"Chen Z, Chen S, Schmid C, et\u00a0al (2023) gsdf: Geometry-driven signed distance functions for 3d hand-object reconstruction. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp 12,890\u201312,900","DOI":"10.1109\/CVPR52729.2023.01239"},{"key":"8884_CR6","doi-asserted-by":"crossref","unstructured":"Cho W, Park G, Woo W (2020) Bare-hand depth inpainting for 3d tracking of hand interacting with object. In: ISMAR, IEEE, pp 251\u2013259","DOI":"10.1109\/ISMAR50242.2020.00048"},{"key":"8884_CR7","doi-asserted-by":"crossref","unstructured":"Doosti B, Naha S, Mirbagheri M, et\u00a0al (2020) Hope-net: a graph-based model for hand-object pose estimation. In: 2020 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","DOI":"10.1109\/CVPR42600.2020.00664"},{"issue":"7","key":"8884_CR8","doi-asserted-by":"publisher","first-page":"1477","DOI":"10.1007\/s00521-012-0844-2","volume":"22","author":"A El-Baz","year":"2013","unstructured":"El-Baz A, Tolba AS (2013) An efficient algorithm for 3d hand gesture recognition using combined neural classifiers. Neural Comput Appl 22(7):1477\u20131484","journal-title":"Neural Comput Appl"},{"issue":"12","key":"8884_CR9","doi-asserted-by":"publisher","first-page":"8533","DOI":"10.1007\/s00521-018-3719-3","volume":"31","author":"L Fang","year":"2019","unstructured":"Fang L, Wu G, Kang W et al (2019) Feature covariance matrix-based dynamic hand gesture recognition. Neural Comput Appl 31(12):8533\u20138546","journal-title":"Neural Comput Appl"},{"key":"8884_CR10","doi-asserted-by":"crossref","unstructured":"Goudie D, Galata A (2017) 3d hand-object pose estimation from depth with convolutional neural networks. In: FG 2017, IEEE, pp 406\u2013413","DOI":"10.1109\/FG.2017.58"},{"key":"8884_CR11","doi-asserted-by":"crossref","unstructured":"Goyal R, Ebrahimi\u00a0Kahou S, Michalski V, et\u00a0al (2017) The\" something something\" video database for learning and evaluating visual common sense. In: Proceedings of the IEEE international conference on computer vision, pp 5842\u20135850","DOI":"10.1109\/ICCV.2017.622"},{"key":"8884_CR12","unstructured":"Hampali S, Rad M, Oberweger M, et\u00a0al (2020) Ho3d competition. https:\/\/competitions.codalab.org\/competitions\/22485"},{"key":"8884_CR13","doi-asserted-by":"crossref","unstructured":"Hampali S, Rad M, Oberweger M, et\u00a0al (2020) Honnotate: a method for 3d annotation of hand and object poses. In: CVPR, pp 3196\u20133206","DOI":"10.1109\/CVPR42600.2020.00326"},{"issue":"4","key":"8884_CR14","first-page":"1","volume":"39","author":"S Han","year":"2020","unstructured":"Han S, Liu B, Cabezas R et al (2020) Megatrack: monochrome egocentric articulated hand-tracking for virtual reality. ACM Trans Grap 39(4):1\u201313","journal-title":"ACM Trans Grap"},{"issue":"2","key":"8884_CR15","doi-asserted-by":"publisher","first-page":"251","DOI":"10.1007\/s00521-013-1481-0","volume":"25","author":"H Hasan","year":"2014","unstructured":"Hasan H, Abdul-Kareem S (2014) Retracted article: human-computer interaction using vision-based hand gesture recognition systems: a survey. Neural Comput Appl 25(2):251\u2013261","journal-title":"Neural Comput Appl"},{"key":"8884_CR16","doi-asserted-by":"crossref","unstructured":"Hasson Y, Varol G, Tzionas D, et\u00a0al (2019) Learning joint reconstruction of hands and manipulated objects. In: CVPR, pp 11,807\u201311,816","DOI":"10.1109\/CVPR.2019.01208"},{"key":"8884_CR17","doi-asserted-by":"crossref","unstructured":"Hasson Y, Tekin B, Bogo F, et\u00a0al (2020) Leveraging photometric consistency over time for sparsely supervised hand-object reconstruction. In: CVPR, pp 571\u2013580","DOI":"10.1109\/CVPR42600.2020.00065"},{"key":"8884_CR18","doi-asserted-by":"crossref","unstructured":"Hasson Y, Varol G, Schmid C et\u00a0al (2021) Towards unconstrained joint hand-object reconstruction from rgb videos. In: 2021 International Conference on 3D Vision (3DV), IEEE, pp 659\u2013668","DOI":"10.1109\/3DV53792.2021.00075"},{"issue":"3","key":"8884_CR19","doi-asserted-by":"publisher","first-page":"385","DOI":"10.1080\/14640748408402169","volume":"36","author":"GW Humphreys","year":"1984","unstructured":"Humphreys GW, Riddoch MJ (1984) Routes to object constancy: implications from neurological impairments of object constancy. Quart J Exp Psychol 36(3):385\u2013415","journal-title":"Quart J Exp Psychol"},{"issue":"18","key":"8884_CR20","doi-asserted-by":"publisher","first-page":"13321","DOI":"10.1007\/s00521-023-08440-0","volume":"35","author":"A Kushwaha","year":"2023","unstructured":"Kushwaha A, Khare A, Prakash O (2023) Micro-network-based deep convolutional neural network for human activity recognition from realistic and multi-view visual data. Neural Comput Appl 35(18):13321\u201313341","journal-title":"Neural Comput Appl"},{"key":"8884_CR21","doi-asserted-by":"crossref","unstructured":"Li J, Xu C, Chen Z, et\u00a0al (2021) Hybrik: A hybrid analytical-neural inverse kinematics solution for 3d human pose and shape estimation. In: CVPR, pp 3383\u20133393","DOI":"10.1109\/CVPR46437.2021.00339"},{"key":"8884_CR22","doi-asserted-by":"publisher","first-page":"251","DOI":"10.1016\/j.patcog.2019.04.026","volume":"93","author":"R Li","year":"2019","unstructured":"Li R, Liu Z, Tan J (2019) A survey on 3d hand pose estimation: cameras, methods, and datasets. Pattern Recognit 93:251\u2013272","journal-title":"Pattern Recognit"},{"issue":"3","key":"8884_CR23","doi-asserted-by":"publisher","first-page":"715","DOI":"10.1007\/s11760-022-02279-z","volume":"17","author":"X Li","year":"2023","unstructured":"Li X, Lin X, Sun Y (2023) Gecm: graph embedded convolution model for hand mesh reconstruction. Signal Image Video Process 17(3):715\u2013723","journal-title":"Signal Image Video Process"},{"key":"8884_CR24","doi-asserted-by":"crossref","unstructured":"Liu C, Li Y, Ma K, et\u00a0al (2021) Learning 3-d human pose estimation from catadioptric videos. In: IJCAI, pp 852\u2013859","DOI":"10.24963\/ijcai.2021\/118"},{"key":"8884_CR25","unstructured":"Liu S, Jiang H, Xu J, et\u00a0al (2021) Semi hand-object. https:\/\/github.com\/stevenlsw\/Semi-Hand-Object"},{"key":"8884_CR26","doi-asserted-by":"crossref","unstructured":"Liu S, Jiang H, Xu J, et\u00a0al (2021) Semi-supervised 3d hand-object poses estimation with interactions in time. In: CVPR, pp 14687\u201314697","DOI":"10.1109\/CVPR46437.2021.01445"},{"key":"8884_CR27","doi-asserted-by":"crossref","unstructured":"Liu Z, Chen H, Feng R, et\u00a0al (2021) Deep dual consecutive network for human pose estimation. In: CVPR, pp 525\u2013534","DOI":"10.1109\/CVPR46437.2021.00059"},{"issue":"2","key":"8884_CR28","doi-asserted-by":"publisher","first-page":"577","DOI":"10.1146\/annurev.ne.19.030196.003045","volume":"19","author":"N Logothetis","year":"1996","unstructured":"Logothetis N (1996) Visual object recognition. Ann Rev Neurosci 19(2):577\u2013621","journal-title":"Ann Rev Neurosci"},{"issue":"7","key":"8884_CR29","doi-asserted-by":"publisher","first-page":"2339","DOI":"10.1007\/s00521-020-05125-w","volume":"33","author":"A Mishra","year":"2021","unstructured":"Mishra A, Sharma S, Kumar S et al (2021) Effect of hand grip actions on object recognition process: a machine learning-based approach for improved motor rehabilitation. Neural Comput Appl 33(7):2339\u20132350","journal-title":"Neural Comput Appl"},{"key":"8884_CR30","doi-asserted-by":"crossref","unstructured":"Park JJ, Florence P, Straub J, et\u00a0al (2019) Deepsdf: Learning continuous signed distance functions for shape representation. In: CVPR, pp 165\u2013174","DOI":"10.1109\/CVPR.2019.00025"},{"issue":"6","key":"8884_CR31","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3130800.3130883","volume":"36","author":"J Romero","year":"2017","unstructured":"Romero J, Tzionas D, Black MJ (2017) Embodied hands: Modeling and capturing hands and bodies together. ToG 36(6):1\u201317","journal-title":"ToG"},{"issue":"6","key":"8884_CR32","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3414685.3417768","volume":"39","author":"B Smith","year":"2020","unstructured":"Smith B, Wu C, Wen H et al (2020) Constraining dense hand surface tracking with elasticity. TOG 39(6):1\u201314","journal-title":"TOG"},{"key":"8884_CR33","doi-asserted-by":"crossref","unstructured":"Spurr A, Iqbal U, Molchanov P, et\u00a0al (2020) Weakly supervised 3d hand pose estimation via biomechanical constraints. In: ECCV, Springer, pp 211\u2013228","DOI":"10.1007\/978-3-030-58520-4_13"},{"key":"8884_CR34","doi-asserted-by":"crossref","unstructured":"Tekin B, Bogo F, Pollefeys M (2019) H+o: Unified egocentric recognition of 3d hand-object poses and interactions. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 4511\u20134520","DOI":"10.1109\/CVPR.2019.00464"},{"key":"8884_CR35","doi-asserted-by":"crossref","unstructured":"Tekin B, Bogo F, Pollefeys M (2019) H+o: Unified egocentric recognition of 3d hand-object poses and interactions. In: CVPR, pp 4511\u20134520","DOI":"10.1109\/CVPR.2019.00464"},{"key":"8884_CR36","doi-asserted-by":"crossref","unstructured":"Wang C, Xu D, Zhu Y, et\u00a0al (2019) Densefusion: 6d object pose estimation by iterative dense fusion. In: CVPR, pp 3343\u20133352","DOI":"10.1109\/CVPR.2019.00346"},{"key":"8884_CR37","doi-asserted-by":"crossref","unstructured":"Wei SE, Ramakrishna V, Kanade T, et\u00a0al (2016) Convolutional pose machines. In: Proceedings of the IEEE conference on Computer Vision and Pattern Recognition, pp 4724\u20134732","DOI":"10.1109\/CVPR.2016.511"},{"key":"8884_CR38","doi-asserted-by":"crossref","unstructured":"Xiong F, Zhang B, Xiao Y, et\u00a0al (2019) A2j: Anchor-to-joint regression network for 3d articulated pose estimation from a single depth image. In: CVPR, pp 793\u2013802","DOI":"10.1109\/ICCV.2019.00088"},{"key":"8884_CR39","doi-asserted-by":"crossref","unstructured":"Yang J, Chang HJ, Lee S, et\u00a0al (2020) Seqhand: Rgb-sequence-based 3d hand pose and shape estimation. In: ECCV, Springer, pp 122\u2013139","DOI":"10.1007\/978-3-030-58610-2_8"},{"key":"8884_CR40","doi-asserted-by":"crossref","unstructured":"Yang L, Li K, Zhan X, et\u00a0al (2022) Artiboost: Boosting articulated 3d hand-object pose estimation via online exploration and synthesis. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp 2750\u20132760","DOI":"10.1109\/CVPR52688.2022.00277"},{"key":"8884_CR41","doi-asserted-by":"crossref","unstructured":"Yang L, Li K, Zhan X, et\u00a0al (2022) Oakink: A large-scale knowledge repository for understanding hand-object interaction. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp 20,953\u201320,962","DOI":"10.1109\/CVPR52688.2022.02028"},{"key":"8884_CR42","doi-asserted-by":"crossref","unstructured":"Ye Y, Gupta A, Tulsiani S (2022) What\u2019s in your hands? 3d reconstruction of generic objects in hands. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp 3895\u20133905","DOI":"10.1109\/CVPR52688.2022.00387"},{"key":"8884_CR43","doi-asserted-by":"crossref","unstructured":"Yuan S, Garcia-Hernando G, Stenger B, et\u00a0al (2018) Depth-based 3d hand pose estimation: From current achievements to future goals. In: CVPR, pp 2636\u20132645","DOI":"10.1109\/CVPR.2018.00279"},{"key":"8884_CR44","doi-asserted-by":"crossref","unstructured":"Yuan Y, Wei SE, Simon T, et\u00a0al (2021) Simpoe: Simulated character control for 3d human pose estimation. In: CVPR, pp 7159\u20137169","DOI":"10.1109\/CVPR46437.2021.00708"},{"key":"8884_CR45","doi-asserted-by":"crossref","unstructured":"Zhang Z, Hu L, Deng X, et\u00a0al (2021) Sequential 3d human pose estimation using adaptive point cloud sampling strategy. In: IJCAI, pp 1330\u20131337","DOI":"10.24963\/ijcai.2021\/184"},{"key":"8884_CR46","doi-asserted-by":"crossref","unstructured":"Zhao Z, Wang T, Xia S, et\u00a0al (2020) Hand-3d-studio: A new multi-view system for 3d hand reconstruction. In: ICASSP, IEEE, pp 2478\u20132482","DOI":"10.1109\/ICASSP40776.2020.9053321"},{"key":"8884_CR47","doi-asserted-by":"crossref","unstructured":"Zhou Y, Habermann M, Xu W, et\u00a0al (2020) Monocular real-time hand shape and motion capture using multi-modal data. In: CVPR, pp 5346\u20135355","DOI":"10.1109\/CVPR42600.2020.00539"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-023-08884-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00521-023-08884-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-023-08884-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,8,30]],"date-time":"2023-08-30T00:24:53Z","timestamp":1693355093000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00521-023-08884-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,7,31]]},"references-count":47,"journal-issue":{"issue":"28","published-print":{"date-parts":[[2023,10]]}},"alternative-id":["8884"],"URL":"https:\/\/doi.org\/10.1007\/s00521-023-08884-4","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"type":"print","value":"0941-0643"},{"type":"electronic","value":"1433-3058"}],"subject":[],"published":{"date-parts":[[2023,7,31]]},"assertion":[{"value":"18 August 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 July 2023","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"31 July 2023","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}