{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,8]],"date-time":"2026-01-08T05:47:18Z","timestamp":1767851238330,"version":"3.49.0"},"publisher-location":"New York, NY, USA","reference-count":64,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,12,10]],"date-time":"2023-12-10T00:00:00Z","timestamp":1702166400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,12,10]]},"DOI":"10.1145\/3610548.3618206","type":"proceedings-article","created":{"date-parts":[[2023,12,11]],"date-time":"2023-12-11T12:28:40Z","timestamp":1702297720000},"page":"1-11","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":13,"title":["SAME: Skeleton-Agnostic Motion Embedding for Character Animation"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-7482-807X","authenticated-orcid":false,"given":"Sunmin","family":"Lee","sequence":"first","affiliation":[{"name":"Seoul National University, South Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4556-5588","authenticated-orcid":false,"given":"Taeho","family":"Kang","sequence":"additional","affiliation":[{"name":"Seoul National University, South Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3694-093X","authenticated-orcid":false,"given":"Jungnam","family":"Park","sequence":"additional","affiliation":[{"name":"Seoul National University, South Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1023-1868","authenticated-orcid":false,"given":"Jehee","family":"Lee","sequence":"additional","affiliation":[{"name":"NCSOFT, South Korea and Seoul National University, South Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5510-6425","authenticated-orcid":false,"given":"Jungdam","family":"Won","sequence":"additional","affiliation":[{"name":"Seoul National University, South Korea"}]}],"member":"320","published-online":{"date-parts":[[2023,12,11]]},"reference":[{"key":"e_1_3_2_2_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/3386569.3392462"},{"key":"e_1_3_2_2_2_1","volume-title":"Learning character-agnostic motion for motion retargeting in 2d. arXiv preprint arXiv:1905.01680","author":"Aberman Kfir","year":"2019","unstructured":"Kfir Aberman, Rundi Wu, Dani Lischinski, Baoquan Chen, and Daniel Cohen-Or. 2019. Learning character-agnostic motion for motion retargeting in 2d. arXiv preprint arXiv:1905.01680 (2019)."},{"key":"e_1_3_2_2_3_1","unstructured":"Adobe. 2021. Mixamo Animation Dataset. https:\/\/www.mixamo.com\/"},{"key":"e_1_3_2_2_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/3272127.3275038"},{"key":"e_1_3_2_2_5_1","unstructured":"Autodesk. 2021. Motion Builder - a 3D character animation software. Autodesk. https:\/\/www.autodesk.com\/"},{"key":"e_1_3_2_2_6_1","unstructured":"Tom\u00a0B. Brown Benjamin Mann Nick Ryder Melanie Subbiah Jared Kaplan Prafulla Dhariwal Arvind Neelakantan Pranav Shyam Girish Sastry Amanda Askell Sandhini Agarwal Ariel Herbert-Voss Gretchen Krueger Tom Henighan Rewon Child Aditya Ramesh Daniel\u00a0M. Ziegler Jeffrey Wu Clemens Winter Christopher Hesse Mark Chen Eric Sigler Mateusz Litwin Scott Gray Benjamin Chess Jack Clark Christopher Berner Sam McCandlish Alec Radford Ilya Sutskever and Dario Amodei. 2020. Language Models are Few-Shot Learners. arxiv:2005.14165\u00a0[cs.CL]"},{"key":"e_1_3_2_2_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/1186822.1073248"},{"key":"e_1_3_2_2_8_1","volume-title":"Proceedings of Pacific Graphics. 32\u201342","author":"Choi Kwang-Jin","year":"1999","unstructured":"Kwang-Jin Choi and Hyeong-Seok Ko. 1999. On-line motion retargetting. In Proceedings of Pacific Graphics. 32\u201342."},{"key":"e_1_3_2_2_9_1","unstructured":"Aakanksha Chowdhery Sharan Narang Jacob Devlin Maarten Bosma Gaurav Mishra Adam Roberts Paul Barham Hyung\u00a0Won Chung Charles Sutton Sebastian Gehrmann Parker Schuh Kensen Shi Sasha Tsvyashchenko Joshua Maynez Abhishek Rao Parker Barnes Yi Tay Noam Shazeer Vinodkumar Prabhakaran Emily Reif Nan Du Ben Hutchinson Reiner Pope James Bradbury Jacob Austin Michael Isard Guy Gur-Ari Pengcheng Yin Toju Duke Anselm Levskaya Sanjay Ghemawat Sunipa Dev Henryk Michalewski Xavier Garcia Vedant Misra Kevin Robinson Liam Fedus Denny Zhou Daphne Ippolito David Luan Hyeontaek Lim Barret Zoph Alexander Spiridonov Ryan Sepassi David Dohan Shivani Agrawal Mark Omernick Andrew\u00a0M. Dai Thanumalayan\u00a0Sankaranarayana Pillai Marie Pellat Aitor Lewkowycz Erica Moreira Rewon Child Oleksandr Polozov Katherine Lee Zongwei Zhou Xuezhi Wang Brennan Saeta Mark Diaz Orhan Firat Michele Catasta Jason Wei Kathy Meier-Hellstern Douglas Eck Jeff Dean Slav Petrov and Noah Fiedel. 2022. PaLM: Scaling Language Modeling with Pathways. arxiv:2204.02311\u00a0[cs.CL]"},{"key":"e_1_3_2_2_10_1","unstructured":"CMU. 2006. CMU Graphics Lab Motion Capture Database. http:\/\/mocap.cs.cmu.edu\/"},{"key":"e_1_3_2_2_11_1","volume-title":"Fast Graph Representation Learning with PyTorch Geometric. In ICLR Workshop on Representation Learning on Graphs and Manifolds.","author":"Fey Matthias","year":"2019","unstructured":"Matthias Fey and Jan\u00a0E. Lenssen. 2019. Fast Graph Representation Learning with PyTorch Geometric. In ICLR Workshop on Representation Learning on Graphs and Manifolds."},{"key":"e_1_3_2_2_12_1","doi-asserted-by":"crossref","unstructured":"Saeed Ghorbani Calden Wloka Ali Etemad Marcus\u00a0A Brubaker and Nikolaus\u00a0F Troje. 2020. Probabilistic character motion synthesis using a hierarchical deep latent variable model. In Computer Graphics Forum Vol.\u00a039. 225\u2013239.","DOI":"10.1111\/cgf.14116"},{"key":"e_1_3_2_2_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/280814.280820"},{"key":"e_1_3_2_2_14_1","doi-asserted-by":"publisher","DOI":"10.5244\/C.31.119"},{"key":"e_1_3_2_2_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/3386569.3392480"},{"key":"e_1_3_2_2_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/3386569.3392480"},{"key":"e_1_3_2_2_17_1","volume-title":"Nemf: Neural motion fields for kinematic animation. arXiv preprint arXiv:2206.03287","author":"He Chengan","year":"2022","unstructured":"Chengan He, Jun Saito, James Zachary, Holly Rushmeier, and Yi Zhou. 2022. Nemf: Neural motion fields for kinematic animation. arXiv preprint arXiv:2206.03287 (2022)."},{"key":"e_1_3_2_2_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/3072959.3073663"},{"key":"e_1_3_2_2_19_1","doi-asserted-by":"crossref","unstructured":"Daniel Holden Jun Saito Taku Komura and Thomas Joyce. 2015. Learning motion manifolds with convolutional autoencoders. In SIGGRAPH Asia 2015 technical briefs. 1\u20134.","DOI":"10.1145\/2820903.2820918"},{"key":"e_1_3_2_2_20_1","volume-title":"A Causal Convolutional Neural Network for Motion Modeling and Synthesis. arXiv preprint arXiv:2101.12276","author":"Hou Shuaiying","year":"2021","unstructured":"Shuaiying Hou, Weiwei Xu, Jinxiang Chai, Congyi Wang, Wenlin Zhuang, Yu Chen, Hujun Bao, and Yangang Wang. 2021. A Causal Convolutional Neural Network for Motion Modeling and Synthesis. arXiv preprint arXiv:2101.12276 (2021)."},{"key":"e_1_3_2_2_21_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i07.6759"},{"key":"e_1_3_2_2_22_1","volume-title":"Motion Puzzle: Arbitrary Motion Style Transfer by Body Part. arXiv preprint arXiv:2202.05274","author":"Jang Deok-Kyeong","year":"2022","unstructured":"Deok-Kyeong Jang, Soomin Park, and Sung-Hee Lee. 2022. Motion Puzzle: Arbitrary Motion Style Transfer by Body Part. arXiv preprint arXiv:2202.05274 (2022)."},{"key":"e_1_3_2_2_23_1","doi-asserted-by":"publisher","DOI":"10.1145\/566570.566607"},{"key":"e_1_3_2_2_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/311535.311539"},{"key":"e_1_3_2_2_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/3272127.3275071"},{"key":"e_1_3_2_2_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/3DV53792.2021.00086"},{"key":"e_1_3_2_2_27_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00371"},{"key":"e_1_3_2_2_28_1","volume-title":"Proceedings of British Machine Vision Conference (BMVC), Vol.\u00a02. 7.","author":"Lim Jongin","year":"2019","unstructured":"Jongin Lim, Hyung\u00a0Jin Chang, and Jin\u00a0Young Choi. 2019. PMnet: Learning of Disentangled Pose and Movement for Unsupervised Motion Retargeting.. In Proceedings of British Machine Vision Conference (BMVC), Vol.\u00a02. 7."},{"key":"e_1_3_2_2_29_1","doi-asserted-by":"publisher","DOI":"10.1145\/3386569.3392422"},{"key":"e_1_3_2_2_30_1","doi-asserted-by":"publisher","DOI":"10.1145\/2816795.2818013"},{"key":"e_1_3_2_2_31_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00554"},{"key":"e_1_3_2_2_32_1","doi-asserted-by":"publisher","DOI":"10.5555\/1324818"},{"key":"e_1_3_2_2_33_1","doi-asserted-by":"publisher","DOI":"10.5555\/1218064.1218083"},{"key":"e_1_3_2_2_34_1","unstructured":"OSU. [n. d.]. OSU ACCAD. https:\/\/accad.osu.edu\/"},{"key":"e_1_3_2_2_35_1","volume-title":"arXiv preprint arXiv:2201.12044","author":"Park Jungnam","year":"2022","unstructured":"Jungnam Park, Sehee Min, Phil\u00a0Sik Chang, Jaedong Lee, Moonseok Park, and Jehee Lee. 2022. Generative GaitNet. arXiv preprint arXiv:2201.12044 (2022)."},{"key":"e_1_3_2_2_36_1","first-page":"8024","article-title":"PyTorch: An Imperative Style, High-Performance Deep Learning Library","volume":"32","author":"Paszke Adam","year":"2019","unstructured":"Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Kopf, Edward Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala. 2019. PyTorch: An Imperative Style, High-Performance Deep Learning Library. In Advances in Neural Information Processing Systems 32. 8024\u20138035.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_2_37_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01123"},{"key":"e_1_3_2_2_38_1","volume-title":"Quaternet: A quaternion-based recurrent model for human motion. arXiv preprint arXiv:1805.06485","author":"Pavllo Dario","year":"2018","unstructured":"Dario Pavllo, David Grangier, and Michael Auli. 2018. Quaternet: A quaternion-based recurrent model for human motion. arXiv preprint arXiv:1805.06485 (2018)."},{"key":"e_1_3_2_2_39_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.01333"},{"key":"e_1_3_2_2_40_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01129"},{"key":"e_1_3_2_2_41_1","doi-asserted-by":"publisher","DOI":"10.1145\/1015706.1015754"},{"key":"e_1_3_2_2_42_1","unstructured":"SFU. 2011. SFU Motion Capture Database. https:\/\/mocap.cs.sfu.ca\/"},{"key":"e_1_3_2_2_43_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01230"},{"key":"e_1_3_2_2_44_1","volume-title":"MotioNet: 3D Human Motion Reconstruction from Monocular Video with Skeleton Consistency. arXiv preprint arXiv:2006.12075","author":"Shi Mingyi","year":"2020","unstructured":"Mingyi Shi, Kfir Aberman, Andreas Aristidou, Taku Komura, Dani Lischinski, Daniel Cohen-Or, and Baoquan Chen. 2020. MotioNet: 3D Human Motion Reconstruction from Monocular Video with Skeleton Consistency. arXiv preprint arXiv:2006.12075 (2020)."},{"key":"e_1_3_2_2_45_1","volume-title":"Motion synthesis and editing in low-dimensional spaces. Computer Animation and Virtual Worlds (CASA 2006) 17","author":"Shin Hyun\u00a0Joon","year":"2006","unstructured":"Hyun\u00a0Joon Shin and Jehee Lee. 2006. Motion synthesis and editing in low-dimensional spaces. Computer Animation and Virtual Worlds (CASA 2006) 17 (2006), 219\u2013227. Issue 3-4."},{"key":"e_1_3_2_2_46_1","doi-asserted-by":"publisher","DOI":"10.1145\/502122.502123"},{"key":"e_1_3_2_2_47_1","unstructured":"SNU. 2013. SNU Motion Database. https:\/\/mrl.snu.ac.kr\/mdb\/"},{"key":"e_1_3_2_2_48_1","doi-asserted-by":"publisher","DOI":"10.1145\/3528223.3530178"},{"key":"e_1_3_2_2_49_1","doi-asserted-by":"publisher","DOI":"10.1109\/38.637269"},{"key":"e_1_3_2_2_50_1","doi-asserted-by":"publisher","DOI":"10.1145\/1037957.1037963"},{"key":"e_1_3_2_2_51_1","volume-title":"Human Motion Diffusion Model. In The Eleventh International Conference on Learning Representations. https:\/\/openreview.net\/forum?id=SJ1kSyO2jwu","author":"Tevet Guy","year":"2023","unstructured":"Guy Tevet, Sigal Raab, Brian Gordon, Yoni Shafir, Daniel Cohen-or, and Amit\u00a0Haim Bermano. 2023. Human Motion Diffusion Model. In The Eleventh International Conference on Learning Representations. https:\/\/openreview.net\/forum?id=SJ1kSyO2jwu"},{"key":"e_1_3_2_2_52_1","unstructured":"Hugo Touvron Thibaut Lavril Gautier Izacard Xavier Martinet Marie-Anne Lachaux Timoth\u00e9e Lacroix Baptiste Rozi\u00e8re Naman Goyal Eric Hambro Faisal Azhar Aurelien Rodriguez Armand Joulin Edouard Grave and Guillaume Lample. 2023. LLaMA: Open and Efficient Foundation Language Models. arxiv:2302.13971\u00a0[cs.CL]"},{"key":"e_1_3_2_2_53_1","doi-asserted-by":"publisher","DOI":"10.5244\/C.31.14"},{"key":"e_1_3_2_2_54_1","volume-title":"Attention is all you need. Advances in neural information processing systems 30","author":"Vaswani Ashish","year":"2017","unstructured":"Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan\u00a0N Gomez, \u0141ukasz Kaiser, and Illia Polosukhin. 2017. Attention is all you need. Advances in neural information processing systems 30 (2017)."},{"key":"e_1_3_2_2_55_1","volume-title":"Graph attention networks. arXiv preprint arXiv:1710.10903","author":"Veli\u010dkovi\u0107 Petar","year":"2017","unstructured":"Petar Veli\u010dkovi\u0107, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Lio, and Yoshua Bengio. 2017. Graph attention networks. arXiv preprint arXiv:1710.10903 (2017)."},{"key":"e_1_3_2_2_56_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00901"},{"key":"e_1_3_2_2_57_1","volume-title":"Gaussian process dynamical models for human motion","author":"Wang M","year":"2007","unstructured":"Jack\u00a0M Wang, David\u00a0J Fleet, and Aaron Hertzmann. 2007. Gaussian process dynamical models for human motion. IEEE transactions on pattern analysis and machine intelligence 30, 2 (2007), 283\u2013298."},{"key":"e_1_3_2_2_58_1","volume-title":"Dynamic graph cnn for learning on point clouds. Acm Transactions On Graphics (tog) 38, 5","author":"Wang Yue","year":"2019","unstructured":"Yue Wang, Yongbin Sun, Ziwei Liu, Sanjay\u00a0E Sarma, Michael\u00a0M Bronstein, and Justin\u00a0M Solomon. 2019. Dynamic graph cnn for learning on point clouds. Acm Transactions On Graphics (tog) 38, 5 (2019), 1\u201312."},{"key":"e_1_3_2_2_59_1","doi-asserted-by":"publisher","DOI":"10.1145\/3355089.3356499"},{"key":"e_1_3_2_2_60_1","volume-title":"Rignet: Neural rigging for articulated characters. arXiv preprint arXiv:2005.00559","author":"Xu Zhan","year":"2020","unstructured":"Zhan Xu, Yang Zhou, Evangelos Kalogerakis, Chris Landreth, and Karan Singh. 2020. Rignet: Neural rigging for articulated characters. arXiv preprint arXiv:2005.00559 (2020)."},{"key":"e_1_3_2_2_61_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.12328"},{"key":"e_1_3_2_2_62_1","volume-title":"PhysDiff: Physics-Guided Human Motion Diffusion Model. arXiv preprint arXiv:2212.02500","author":"Yuan Ye","year":"2022","unstructured":"Ye Yuan, Jiaming Song, Umar Iqbal, Arash Vahdat, and Jan Kautz. 2022. PhysDiff: Physics-Guided Human Motion Diffusion Model. arXiv preprint arXiv:2212.02500 (2022)."},{"key":"e_1_3_2_2_63_1","doi-asserted-by":"publisher","DOI":"10.1145\/3274247.3274502"},{"key":"e_1_3_2_2_64_1","volume-title":"On the Continuity of Rotation Representations in Neural Networks. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR).","author":"Zhou Yi","year":"2019","unstructured":"Yi Zhou, Connelly Barnes, Lu Jingwan, Yang Jimei, and Li Hao. 2019. On the Continuity of Rotation Representations in Neural Networks. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)."}],"event":{"name":"SA '23: SIGGRAPH Asia 2023","location":"Sydney NSW Australia","acronym":"SA '23","sponsor":["SIGGRAPH ACM Special Interest Group on Computer Graphics and Interactive Techniques"]},"container-title":["SIGGRAPH Asia 2023 Conference Papers"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3610548.3618206","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3610548.3618206","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,21]],"date-time":"2025-08-21T09:34:07Z","timestamp":1755768847000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3610548.3618206"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,12,10]]},"references-count":64,"alternative-id":["10.1145\/3610548.3618206","10.1145\/3610548"],"URL":"https:\/\/doi.org\/10.1145\/3610548.3618206","relation":{},"subject":[],"published":{"date-parts":[[2023,12,10]]},"assertion":[{"value":"2023-12-11","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}