{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,11,15]],"date-time":"2024-11-15T05:45:35Z","timestamp":1731649535244,"version":"3.28.0"},"reference-count":45,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2024,4,1]],"date-time":"2024-04-01T00:00:00Z","timestamp":1711929600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2024,4,1]],"date-time":"2024-04-01T00:00:00Z","timestamp":1711929600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2024,4,1]],"date-time":"2024-04-01T00:00:00Z","timestamp":1711929600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2024,4,1]],"date-time":"2024-04-01T00:00:00Z","timestamp":1711929600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2024,4,1]],"date-time":"2024-04-01T00:00:00Z","timestamp":1711929600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2024,4,1]],"date-time":"2024-04-01T00:00:00Z","timestamp":1711929600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,4,1]],"date-time":"2024-04-01T00:00:00Z","timestamp":1711929600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100012434","name":"Middle-aged and Young Teachers' Basic Ability Promotion Project of Guangxi","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100012434","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004607","name":"Guangxi Natural Science Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100004607","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Journal of Visual Communication and Image Representation"],"published-print":{"date-parts":[[2024,4]]},"DOI":"10.1016\/j.jvcir.2024.104129","type":"journal-article","created":{"date-parts":[[2024,3,27]],"date-time":"2024-03-27T04:03:14Z","timestamp":1711512194000},"page":"104129","update-policy":"http:\/\/dx.doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["3D hand reconstruction via aggregating intra and inter graphs guided by prior knowledge for hand-object interaction scenario"],"prefix":"10.1016","volume":"100","author":[{"ORCID":"http:\/\/orcid.org\/0000-0002-4733-4732","authenticated-orcid":false,"given":"Feng","family":"Shuang","sequence":"first","affiliation":[]},{"given":"Wenbo","family":"He","sequence":"additional","affiliation":[]},{"ORCID":"http:\/\/orcid.org\/0000-0002-5034-8721","authenticated-orcid":false,"given":"Shaodong","family":"Li","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.jvcir.2024.104129_b1","series-title":"2007 IEEE International Conference on Image Processing","first-page":"V","article-title":"Natural human-machine interface using an interactive virtual blackboard","volume":"Vol. 5","author":"Conci","year":"2007"},{"issue":"11","key":"10.1016\/j.jvcir.2024.104129_b2","doi-asserted-by":"crossref","DOI":"10.1002\/adfm.202008936","article-title":"Wearable sensors-enabled human\u2013machine interaction systems: from design to application","volume":"31","author":"Yin","year":"2021","journal-title":"Adv. Funct. Mater."},{"issue":"4","key":"10.1016\/j.jvcir.2024.104129_b3","doi-asserted-by":"crossref","DOI":"10.1145\/3386569.3392452","article-title":"MEgATrack: monochrome egocentric articulated hand-tracking for virtual reality","volume":"39","author":"Han","year":"2020","journal-title":"ACM Trans. Graph. (ToG)"},{"key":"10.1016\/j.jvcir.2024.104129_b4","series-title":"2016 International Conference on Collaboration Technologies and Systems","first-page":"597","article-title":"Body ownership in virtual reality","author":"Jung","year":"2016"},{"issue":"4","key":"10.1016\/j.jvcir.2024.104129_b5","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3306346.3322958","article-title":"Real-time pose and shape reconstruction of two interacting hands with a single depth camera","volume":"38","author":"Mueller","year":"2019","journal-title":"ACM Trans. Graph. (ToG)"},{"issue":"6","key":"10.1016\/j.jvcir.2024.104129_b6","first-page":"1","article-title":"Rgb2hands: real-time tracking of 3d hand interactions from monocular rgb video","volume":"39","author":"Wang","year":"2020","journal-title":"ACM Trans. Graph. (ToG)"},{"key":"10.1016\/j.jvcir.2024.104129_b7","series-title":"Computer Vision\u2013ECCV 2020 Workshops: Glasgow, UK, August 23\u201328, 2020, Proceedings, Part II 16","first-page":"278","article-title":"A multi-modal machine learning approach and toolkit to automate recognition of early stages of dementia among british sign language users","author":"Liang","year":"2020"},{"key":"10.1016\/j.jvcir.2024.104129_b8","doi-asserted-by":"crossref","unstructured":"A. Boukhayma, R.d. Bem, P.H. Torr, 3d hand shape and pose from images in the wild, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2019, pp. 10843\u201310852.","DOI":"10.1109\/CVPR.2019.01110"},{"key":"10.1016\/j.jvcir.2024.104129_b9","doi-asserted-by":"crossref","unstructured":"Y. Chen, Z. Tu, D. Kang, L. Bao, Y. Zhang, X. Zhe, R. Chen, J. Yuan, Model-based 3d hand reconstruction via self-supervised learning, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2021, pp. 10451\u201310460.","DOI":"10.1109\/CVPR46437.2021.01031"},{"key":"10.1016\/j.jvcir.2024.104129_b10","doi-asserted-by":"crossref","unstructured":"L. Ge, Z. Ren, Y. Li, Z. Xue, Y. Wang, J. Cai, J. Yuan, 3d hand shape and pose estimation from a single rgb image, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2019, pp. 10833\u201310842.","DOI":"10.1109\/CVPR.2019.01109"},{"key":"10.1016\/j.jvcir.2024.104129_b11","doi-asserted-by":"crossref","unstructured":"J. Park, Y. Oh, G. Moon, H. Choi, K.M. Lee, Handoccnet: Occlusion-robust 3d hand mesh estimation network, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2022, pp. 1496\u20131505.","DOI":"10.1109\/CVPR52688.2022.00155"},{"year":"2022","series-title":"Embodied hands: Modeling and capturing hands and bodies together","author":"Romero","key":"10.1016\/j.jvcir.2024.104129_b12"},{"key":"10.1016\/j.jvcir.2024.104129_b13","series-title":"Computer Vision\u2013ECCV 2020: 16th European Conference, Glasgow, UK, August 23\u201328, 2020, Proceedings, Part VII 16","first-page":"769","article-title":"Pose2mesh: Graph convolutional network for 3d human pose and mesh recovery from a 2d human pose","author":"Choi","year":"2020"},{"key":"10.1016\/j.jvcir.2024.104129_b14","doi-asserted-by":"crossref","unstructured":"S. Hampali, S.D. Sarkar, M. Rad, V. Lepetit, Keypoint transformer: Solving joint identification in challenging hands and object interactions for accurate 3d pose estimation, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2022, pp. 11090\u201311100.","DOI":"10.1109\/CVPR52688.2022.01081"},{"key":"10.1016\/j.jvcir.2024.104129_b15","doi-asserted-by":"crossref","unstructured":"N. Kolotouros, G. Pavlakos, K. Daniilidis, Convolutional mesh regression for single-image human shape reconstruction, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2019, pp. 4501\u20134510.","DOI":"10.1109\/CVPR.2019.00463"},{"key":"10.1016\/j.jvcir.2024.104129_b16","doi-asserted-by":"crossref","unstructured":"K. Lin, L. Wang, Z. Liu, End-to-end human pose and mesh reconstruction with transformers, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2021, pp. 1954\u20131963.","DOI":"10.1109\/CVPR46437.2021.00199"},{"key":"10.1016\/j.jvcir.2024.104129_b17","doi-asserted-by":"crossref","unstructured":"S. Liu, H. Jiang, J. Xu, S. Liu, X. Wang, Semi-supervised 3d hand-object poses estimation with interactions in time, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2021, pp. 14687\u201314697.","DOI":"10.1109\/CVPR46437.2021.01445"},{"key":"10.1016\/j.jvcir.2024.104129_b18","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1016\/j.neucom.2021.12.013","article-title":"3D interacting hand pose and shape estimation from a single RGB image","volume":"474","author":"Gao","year":"2022","journal-title":"Neurocomputing"},{"key":"10.1016\/j.jvcir.2024.104129_b19","doi-asserted-by":"crossref","unstructured":"L. Huang, J. Tan, J. Meng, J. Liu, J. Yuan, Hot-net: Non-autoregressive transformer for 3d hand-object pose estimation, in: Proceedings of the 28th ACM International Conference on Multimedia, 2020, pp. 3136\u20133145.","DOI":"10.1145\/3394171.3413775"},{"key":"10.1016\/j.jvcir.2024.104129_b20","doi-asserted-by":"crossref","unstructured":"Z. Yu, C. Li, L. Yang, X. Zheng, M.B. Mi, G.H. Lee, A. Yao, Overcoming the Trade-off Between Accuracy and Plausibility in 3D Hand Shape Reconstruction, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2023, pp. 544\u2013553.","DOI":"10.1109\/CVPR52729.2023.00060"},{"key":"10.1016\/j.jvcir.2024.104129_b21","series-title":"2021 13th International Conference on Knowledge and Systems Engineering","first-page":"1","article-title":"Sst-gcn: Structure aware spatial-temporal gcn for 3d hand pose estimation","author":"Le","year":"2021"},{"key":"10.1016\/j.jvcir.2024.104129_b22","series-title":"Computer Vision\u2013ECCV 2020: 16th European Conference, Glasgow, UK, August 23\u201328, 2020, Proceedings, Part VII 16","first-page":"752","article-title":"I2l-meshnet: Image-to-lixel prediction network for accurate 3d human pose and mesh estimation from a single rgb image","author":"Moon","year":"2020"},{"key":"10.1016\/j.jvcir.2024.104129_b23","doi-asserted-by":"crossref","unstructured":"L. Zhao, X. Peng, Y. Tian, M. Kapadia, D.N. Metaxas, Semantic graph convolutional networks for 3d human pose regression, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2019, pp. 3425\u20133435.","DOI":"10.1109\/CVPR.2019.00354"},{"key":"10.1016\/j.jvcir.2024.104129_b24","doi-asserted-by":"crossref","unstructured":"X. Tang, T. Wang, C.-W. Fu, Towards accurate alignment in real-time 3d hand-mesh reconstruction, in: Proceedings of the IEEE\/CVF International Conference on Computer Vision, 2021, pp. 11698\u201311707.","DOI":"10.1109\/ICCV48922.2021.01149"},{"key":"10.1016\/j.jvcir.2024.104129_b25","unstructured":"T.H.E. Tse, K.I. Kim, A. Leonardis, H.J. Chang, Collaborative learning for hand and object reconstruction with attention-guided graph convolution, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2022, pp. 1664\u20131674."},{"key":"10.1016\/j.jvcir.2024.104129_b26","doi-asserted-by":"crossref","unstructured":"Y.-W. Chao, W. Yang, Y. Xiang, P. Molchanov, A. Handa, J. Tremblay, Y.S. Narang, K. Van Wyk, U. Iqbal, S. Birchfield, et al., DexYCB: A benchmark for capturing hand grasping of objects, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2021, pp. 9044\u20139053.","DOI":"10.1109\/CVPR46437.2021.00893"},{"key":"10.1016\/j.jvcir.2024.104129_b27","doi-asserted-by":"crossref","unstructured":"S.H. Shivakumar, M. Rad, M. Oberweger, V. Lepetit, Honnotate: A Method for 3D Annotation of Hand and Object Poses, in: 2020 IEEE\/CVF Conference on Computer Vision and Pattern Recognition: CVPR 2020, 2020, pp. 3193\u20133203.","DOI":"10.1109\/CVPR42600.2020.00326"},{"key":"10.1016\/j.jvcir.2024.104129_b28","doi-asserted-by":"crossref","unstructured":"X. Zhang, Q. Li, H. Mo, W. Zhang, W. Zheng, End-to-end hand mesh recovery from a monocular rgb image, in: Proceedings of the IEEE\/CVF International Conference on Computer Vision, 2019, pp. 2354\u20132364.","DOI":"10.1109\/ICCV.2019.00244"},{"key":"10.1016\/j.jvcir.2024.104129_b29","doi-asserted-by":"crossref","unstructured":"Z. Lin, C. Ding, H. Yao, Z. Kuang, S. Huang, Harmonious Feature Learning for Interactive Hand-Object Pose Estimation, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2023, pp. 12989\u201312998.","DOI":"10.1109\/CVPR52729.2023.01248"},{"key":"10.1016\/j.jvcir.2024.104129_b30","doi-asserted-by":"crossref","unstructured":"D. Kulon, R.A. Guler, I. Kokkinos, M.M. Bronstein, S. Zafeiriou, Weakly-supervised mesh-convolutional hand reconstruction in the wild, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2020, pp. 4990\u20135000.","DOI":"10.1109\/CVPR42600.2020.00504"},{"key":"10.1016\/j.jvcir.2024.104129_b31","doi-asserted-by":"crossref","unstructured":"R. Wang, W. Mao, H. Li, Interacting Hand-Object Pose Estimation via Dense Mutual Attention, in: Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision, 2023, pp. 5735\u20135745.","DOI":"10.1109\/WACV56688.2023.00569"},{"key":"10.1016\/j.jvcir.2024.104129_b32","doi-asserted-by":"crossref","unstructured":"L. Huang, C.-C. Lin, K. Lin, L. Liang, L. Wang, J. Yuan, Z. Liu, Neural Voting Field for Camera-Space 3D Hand Pose Estimation, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2023, pp. 8969\u20138978.","DOI":"10.1109\/CVPR52729.2023.00866"},{"key":"10.1016\/j.jvcir.2024.104129_b33","doi-asserted-by":"crossref","unstructured":"H. Xu, T. Wang, X. Tang, C.-W. Fu, H2ONet: Hand-Occlusion-and-Orientation-Aware Network for Real-Time 3D Hand Mesh Reconstruction, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2023, pp. 17048\u201317058.","DOI":"10.1109\/CVPR52729.2023.01635"},{"key":"10.1016\/j.jvcir.2024.104129_b34","doi-asserted-by":"crossref","unstructured":"B. Doosti, S. Naha, M. Mirbagheri, D.J. Crandall, Hope-net: A graph-based model for hand-object pose estimation, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2020, pp. 6608\u20136617.","DOI":"10.1109\/CVPR42600.2020.00664"},{"key":"10.1016\/j.jvcir.2024.104129_b35","doi-asserted-by":"crossref","unstructured":"Y. Wang, L. Chen, J. Li, X. Zhang, HandGCNFormer: A Novel Topology-Aware Transformer Network for 3D Hand Pose Estimation, in: Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision, 2023, pp. 5675\u20135684.","DOI":"10.1109\/WACV56688.2023.00563"},{"key":"10.1016\/j.jvcir.2024.104129_b36","doi-asserted-by":"crossref","unstructured":"K. He, X. Zhang, S. Ren, J. Sun, Deep residual learning for image recognition, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2016, pp. 770\u2013778.","DOI":"10.1109\/CVPR.2016.90"},{"key":"10.1016\/j.jvcir.2024.104129_b37","doi-asserted-by":"crossref","unstructured":"T.-Y. Lin, P. Doll\u00e1r, R. Girshick, K. He, B. Hariharan, S. Belongie, Feature pyramid networks for object detection, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2017, pp. 2117\u20132125.","DOI":"10.1109\/CVPR.2017.106"},{"key":"10.1016\/j.jvcir.2024.104129_b38","doi-asserted-by":"crossref","first-page":"166","DOI":"10.1109\/TMM.2020.3047552","article-title":"Differentiable spatial regression: A novel method for 3D hand pose estimation","volume":"24","author":"Zhang","year":"2020","journal-title":"IEEE Trans. Multimed."},{"key":"10.1016\/j.jvcir.2024.104129_b39","doi-asserted-by":"crossref","unstructured":"Z. Jiang, H. Rahmani, S. Black, B.M. Williams, A Probabilistic Attention Model with Occlusion-aware Texture Regression for 3D Hand Reconstruction from a Single RGB Image, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2023, pp. 758\u2013767.","DOI":"10.1109\/CVPR52729.2023.00080"},{"key":"10.1016\/j.jvcir.2024.104129_b40","doi-asserted-by":"crossref","unstructured":"L. Yang, K. Li, X. Zhan, J. Lv, W. Xu, J. Li, C. Lu, 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, 2022, pp. 2750\u20132760.","DOI":"10.1109\/CVPR52688.2022.00277"},{"key":"10.1016\/j.jvcir.2024.104129_b41","doi-asserted-by":"crossref","unstructured":"Y. Hasson, G. Varol, D. Tzionas, I. Kalevatykh, M.J. Black, I. Laptev, C. Schmid, Learning joint reconstruction of hands and manipulated objects, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2019, pp. 11807\u201311816.","DOI":"10.1109\/CVPR.2019.01208"},{"key":"10.1016\/j.jvcir.2024.104129_b42","doi-asserted-by":"crossref","unstructured":"P. Chen, Y. Chen, D. Yang, F. Wu, Q. Li, Q. Xia, Y. Tan, I2uv-handnet: Image-to-uv prediction network for accurate and high-fidelity 3d hand mesh modeling, in: Proceedings of the IEEE\/CVF International Conference on Computer Vision, 2021, pp. 12929\u201312938.","DOI":"10.1109\/ICCV48922.2021.01269"},{"key":"10.1016\/j.jvcir.2024.104129_b43","series-title":"European Conference on Computer Vision","first-page":"211","article-title":"Weakly supervised 3d hand pose estimation via biomechanical constraints","author":"Spurr","year":"2020"},{"key":"10.1016\/j.jvcir.2024.104129_b44","doi-asserted-by":"crossref","unstructured":"X. Chen, Y. Liu, Y. Dong, X. Zhang, C. Ma, Y. Xiong, Y. Zhang, X. Guo, Mobrecon: Mobile-friendly hand mesh reconstruction from monocular image, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2022, pp. 20544\u201320554.","DOI":"10.1109\/CVPR52688.2022.01989"},{"year":"2014","series-title":"Adam: A method for stochastic optimization","author":"Kingma","key":"10.1016\/j.jvcir.2024.104129_b45"}],"container-title":["Journal of Visual Communication and Image Representation"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1047320324000841?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1047320324000841?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2024,11,15]],"date-time":"2024-11-15T02:37:39Z","timestamp":1731638259000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1047320324000841"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,4]]},"references-count":45,"alternative-id":["S1047320324000841"],"URL":"https:\/\/doi.org\/10.1016\/j.jvcir.2024.104129","relation":{},"ISSN":["1047-3203"],"issn-type":[{"type":"print","value":"1047-3203"}],"subject":[],"published":{"date-parts":[[2024,4]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"3D hand reconstruction via aggregating intra and inter graphs guided by prior knowledge for hand-object interaction scenario","name":"articletitle","label":"Article Title"},{"value":"Journal of Visual Communication and Image Representation","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.jvcir.2024.104129","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2024 Elsevier Inc. All rights reserved.","name":"copyright","label":"Copyright"}],"article-number":"104129"}}