{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T13:12:02Z","timestamp":1783948322931,"version":"3.55.0"},"publisher-location":"Singapore","reference-count":24,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819697939","type":"print"},{"value":"9789819697946","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"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":[],"published-print":{"date-parts":[[2025]]},"DOI":"10.1007\/978-981-96-9794-6_7","type":"book-chapter","created":{"date-parts":[[2025,7,14]],"date-time":"2025-07-14T06:12:38Z","timestamp":1752473558000},"page":"72-83","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["BTPose: 3D Pose Estimation from Bone to Pose with Efficient Multi-hypothesis Aggregation"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-9871-5504","authenticated-orcid":false,"given":"Jingtian","family":"Li","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2565-6482","authenticated-orcid":false,"given":"Yi","family":"Wu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1164-9895","authenticated-orcid":false,"given":"Shangfei","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-6479-5105","authenticated-orcid":false,"given":"Guoming","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7875-3809","authenticated-orcid":false,"given":"Meng","family":"Mao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-4319-0358","authenticated-orcid":false,"given":"Linxiang","family":"Tan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,7,15]]},"reference":[{"key":"7_CR1","unstructured":"Menache, A.: Understanding Motion Capture for Computer Animation and Video Games. Morgan Kaufmann (2000)"},{"issue":"10","key":"7_CR2","doi-asserted-by":"publisher","first-page":"1369","DOI":"10.1109\/TVCG.2010.241","volume":"17","author":"N Hagbi","year":"2010","unstructured":"Hagbi, N., Bergig, O., El-Sana, J., Billinghurst, M.: Shape recognition and pose estimation for mobile augmented reality. IEEE Trans. Vis. Comput. Graph. 17(10), 1369\u20131379 (2010)","journal-title":"IEEE Trans. Vis. Comput. Graph."},{"issue":"5","key":"7_CR3","doi-asserted-by":"publisher","first-page":"1110","DOI":"10.1109\/TMM.2013.2246148","volume":"15","author":"Z Ren","year":"2013","unstructured":"Ren, Z., Yuan, J., Meng, J., Zhang, Z.: Robust part-based hand gesture recognition using Kinect sensor. IEEE Trans. Multimed. 15(5), 1110\u20131120 (2013)","journal-title":"IEEE Trans. Multimed."},{"key":"7_CR4","doi-asserted-by":"crossref","unstructured":"Wang, J., et al.: Deep high-resolution representation learning for visual recognition. IEEE Trans. Pattern Anal. Mach. Intell. 43(10), 3349\u20133364 (2020)","DOI":"10.1109\/TPAMI.2020.2983686"},{"key":"7_CR5","doi-asserted-by":"crossref","unstructured":"Chen, Y., Wang, Z., Peng, Y., Zhang, Z., Yu, G., Sun, J.: Cascaded pyramid network for multi-person pose estimation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 7103\u20137112 (2018)","DOI":"10.1109\/CVPR.2018.00742"},{"key":"7_CR6","doi-asserted-by":"crossref","unstructured":"Pavllo, D., Feichtenhofer, C., Grangier, D., Auli, M.: 3D human pose estimation in video with temporal convolutions and semi-supervised training. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 7753\u20137762 (2019)","DOI":"10.1109\/CVPR.2019.00794"},{"key":"7_CR7","doi-asserted-by":"crossref","unstructured":"Lee, K., Lee, I., Lee, S.: Propagating LSTM: 3D pose estimation based on joint interdependency. In: Proceedings of the European Conference on Computer Vision (ECCV), pp. 119\u2013135 (2018)","DOI":"10.1007\/978-3-030-01234-2_8"},{"key":"7_CR8","doi-asserted-by":"crossref","unstructured":"Zhang, J., Tu, Z., Yang, J., Chen, Y., Yuan, J.: MixSTE: Seq2Seq mixed spatio-temporal encoder for 3D human pose estimation in video. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 13232\u201313242 (2022)","DOI":"10.1109\/CVPR52688.2022.01288"},{"key":"7_CR9","doi-asserted-by":"crossref","unstructured":"Graves, A., Graves, A.: Long short-term memory. In: Supervised Sequence Labelling with Recurrent Neural Networks, pp. 37\u201345 (2012)","DOI":"10.1007\/978-3-642-24797-2_4"},{"key":"7_CR10","unstructured":"Vaswani, A., et al.: Attention is all you need. In: Advances in Neural Information Processing Systems, vol. 30 (2017)"},{"issue":"1","key":"7_CR11","doi-asserted-by":"publisher","first-page":"198","DOI":"10.1109\/TCSVT.2021.3057267","volume":"32","author":"T Chen","year":"2021","unstructured":"Chen, T., Fang, C., Shen, X., Zhu, Y., Chen, Z., Luo, J.: Anatomy-aware 3D human pose estimation with bone-based pose decomposition. IEEE Trans. Circuits Syst. Video Technol. 32(1), 198\u2013209 (2021)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"issue":"2","key":"7_CR12","doi-asserted-by":"publisher","first-page":"784","DOI":"10.1109\/TCDS.2022.3185146","volume":"15","author":"G Wang","year":"2022","unstructured":"Wang, G., Zeng, H., Wang, Z., Liu, Z., Wang, H.: Motion projection consistency-based 3-D human pose estimation with virtual bones from monocular videos. IEEE Trans. Cogn. Dev. Syst. 15(2), 784\u2013793 (2022)","journal-title":"IEEE Trans. Cogn. Dev. Syst."},{"key":"7_CR13","doi-asserted-by":"crossref","unstructured":"Cai, Q., Hu, X., Hou, S., Yao, L., Huang, Y.: Disentangled diffusion-based 3D human pose estimation with hierarchical spatial and temporal denoiser. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 38, no. 2, pp. 882\u2013890 (2024)","DOI":"10.1609\/aaai.v38i2.27847"},{"key":"7_CR14","doi-asserted-by":"crossref","unstructured":"Shan, W., et al.: Diffusion-based 3D human pose estimation with multi-hypothesis aggregation. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 14761\u201314771 (2023)","DOI":"10.1109\/ICCV51070.2023.01356"},{"key":"7_CR15","doi-asserted-by":"crossref","unstructured":"Tang, Z., Qiu, Z., Hao, Y., Hong, R., Yao, T.: 3D human pose estimation with spatio-temporal criss-cross attention. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 4790\u20134799 (2023)","DOI":"10.1109\/CVPR52729.2023.00464"},{"key":"7_CR16","doi-asserted-by":"crossref","unstructured":"Xu, J., Guo, Y., Peng, Y.: Finepose: fine-grained prompt-driven 3D human pose estimation via diffusion models. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 561\u2013570 (2024)","DOI":"10.1109\/CVPR52733.2024.00060"},{"key":"7_CR17","doi-asserted-by":"crossref","unstructured":"Zhang, J., Chen, Y., Tu, Z.: Uncertainty-aware 3D human pose estimation from monocular video. In: Proceedings of the 30th ACM International Conference on Multimedia, pp. 5102\u20135113 (2022)","DOI":"10.1145\/3503161.3547773"},{"key":"7_CR18","doi-asserted-by":"crossref","unstructured":"Li, W., Liu, H., Tang, H., Wang, P., Van Gool, L.: Mhformer: multi-hypothesis transformer for 3D human pose estimation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 13147\u201313156 (2022)","DOI":"10.1109\/CVPR52688.2022.01280"},{"key":"7_CR19","unstructured":"Ho, J., Jain, A., Abbeel, P.: Denoising diffusion probabilistic models. In: Advances in Neural Information Processing Systems, vol. 33, pp. 6840\u20136851 (2020)"},{"key":"7_CR20","unstructured":"Song, J., Meng, C., Ermon, S.: Denoising diffusion implicit models. arXiv preprint arXiv:2010.02502 (2020)"},{"key":"7_CR21","doi-asserted-by":"crossref","unstructured":"Ionescu, C., Li, F., Sminchisescu, C.: Latent structured models for human pose estimation. In: 2011 International Conference on Computer Vision, pp. 2220\u20132227. IEEE (2011)","DOI":"10.1109\/ICCV.2011.6126500"},{"key":"7_CR22","doi-asserted-by":"crossref","unstructured":"Mehta, D., et al.: Monocular 3D human pose estimation in the wild using improved CNN supervision. In: 2017 International Conference on 3D Vision, pp. 506\u2013516. IEEE (2017)","DOI":"10.1109\/3DV.2017.00064"},{"key":"7_CR23","unstructured":"Paszke, A., et al.: PyTorch: an imperative style, high-performance deep learning library. In: Advances in Neural Information Processing Systems, vol. 32 (2019)"},{"key":"7_CR24","unstructured":"Loshchilov, I., Hutter, F.: Decoupled weight decay regularization. arXiv preprint arXiv:1711.05101 (2017)"}],"container-title":["Lecture Notes in Computer Science","Advanced Intelligent Computing Technology and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-96-9794-6_7","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T12:42:36Z","timestamp":1783946556000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-96-9794-6_7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9789819697939","9789819697946"],"references-count":24,"URL":"https:\/\/doi.org\/10.1007\/978-981-96-9794-6_7","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"15 July 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICIC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligent Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Ningbo","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 July 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29 July 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icic2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.ic-icc.cn\/icg\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}