{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T15:46:59Z","timestamp":1774021619824,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":73,"publisher":"ACM","funder":[{"DOI":"10.13039\/501100003977","name":"Israel Science Foundation","doi-asserted-by":"publisher","award":["1073\/21"],"award-info":[{"award-number":["1073\/21"]}],"id":[{"id":"10.13039\/501100003977","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,8,10]]},"DOI":"10.1145\/3721238.3730654","type":"proceedings-article","created":{"date-parts":[[2025,7,23]],"date-time":"2025-07-23T08:40:47Z","timestamp":1753260047000},"page":"1-11","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["CageNet: A Meta-Framework for Learning on Wild Meshes"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9126-1617","authenticated-orcid":false,"given":"Michal","family":"Edelstein","sequence":"first","affiliation":[{"name":"Technion - Israel Institute of Technology, Haifa, Israel"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-1753-4485","authenticated-orcid":false,"given":"Hsueh-Ti Derek","family":"Liu","sequence":"additional","affiliation":[{"name":"Roblox, Vancouver, Canada and University of British Columbia, Vancouver, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1732-2327","authenticated-orcid":false,"given":"Mirela","family":"Ben-Chen","sequence":"additional","affiliation":[{"name":"Technion - Israel Institute of Technology, Haifa, Israel"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2025,7,27]]},"reference":[{"key":"e_1_3_3_2_2_1","volume-title":"Autodesk Maya","author":"Inc. Autodesk,","year":"2024","unstructured":"Autodesk, Inc.2024. Autodesk Maya. https:\/\/www.autodesk.com Software."},{"key":"e_1_3_3_2_3_1","doi-asserted-by":"crossref","unstructured":"Seungbae Bang and Sung-Hee Lee. 2018. Spline Interface for Intuitive Skinning Weight Editing. ACM Trans. Graph. 37 5 (2018) 174. https:\/\/doi.org\/10.1145\/3186565","DOI":"10.1145\/3186565"},{"key":"e_1_3_3_2_4_1","doi-asserted-by":"crossref","unstructured":"Gavin Barill Neil\u00a0G Dickson Ryan Schmidt David\u00a0IW Levin and Alec Jacobson. 2018. Fast winding numbers for soups and clouds. ACM Transactions on Graphics (TOG) 37 4 (2018) 1\u201312.","DOI":"10.1145\/3197517.3201337"},{"key":"e_1_3_3_2_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/1599470.1599479"},{"key":"e_1_3_3_2_6_1","unstructured":"Blender Foundation. 2025. Blender \u2013 a 3D Modelling and Rendering Package. http:\/\/www.blender.org"},{"key":"e_1_3_3_2_7_1","unstructured":"Davide Boscaini Jonathan Masci Emanuele Rodol\u00e0 and Michael Bronstein. 2016. Learning shape correspondence with anisotropic convolutional neural networks. Advances in neural information processing systems 29 (2016)."},{"key":"e_1_3_3_2_8_1","doi-asserted-by":"crossref","unstructured":"Michael\u00a0M. Bronstein Joan Bruna Yann LeCun Arthur Szlam and Pierre Vandergheynst. 2017. Geometric Deep Learning: Going beyond Euclidean data. IEEE Signal Process. Mag. 34 4 (2017) 18\u201342.","DOI":"10.1109\/MSP.2017.2693418"},{"key":"e_1_3_3_2_9_1","doi-asserted-by":"crossref","unstructured":"Alfred\u00a0M Bruckstein David\u00a0L Donoho and Michael Elad. 2009. From sparse solutions of systems of equations to sparse modeling of signals and images. SIAM review 51 1 (2009) 34\u201381.","DOI":"10.1137\/060657704"},{"key":"e_1_3_3_2_10_1","volume-title":"ShapeNet: An Information-Rich 3D Model Repository","author":"Chang Angel\u00a0X.","year":"2015","unstructured":"Angel\u00a0X. Chang, Thomas Funkhouser, Leonidas Guibas, Pat Hanrahan, Qixing Huang, Zimo Li, Silvio Savarese, Manolis Savva, Shuran Song, Hao Su, Jianxiong Xiao, Li Yi, and Fisher Yu. 2015. ShapeNet: An Information-Rich 3D Model Repository. Technical Report arXiv:https:\/\/arXiv.org\/abs\/1512.03012 [cs.GR]. Stanford University \u2014 Princeton University \u2014 Toyota Technological Institute at Chicago."},{"key":"e_1_3_3_2_11_1","doi-asserted-by":"crossref","unstructured":"Lu Chen Jin Huang Hanqiu Sun and Hujun Bao. 2010. Cage-based deformation transfer. Computers & Graphics 34 2 (2010) 107\u2013118.","DOI":"10.1016\/j.cag.2010.01.003"},{"key":"e_1_3_3_2_12_1","first-page":"129","volume-title":"Eurographics Italian chapter conference","author":"Cignoni Paolo","year":"2008","unstructured":"Paolo Cignoni, Marco Callieri, Massimiliano Corsini, Matteo Dellepiane, Fabio Ganovelli, Guido Ranzuglia, et\u00a0al. 2008. Meshlab: an open-source mesh processing tool.. In Eurographics Italian chapter conference , Vol.\u00a02008. Salerno, Italy, 129\u2013136."},{"key":"e_1_3_3_2_13_1","doi-asserted-by":"crossref","unstructured":"Fernando de Goes and Mathieu Desbrun. 2024. Stochastic Computation of Barycentric Coordinates. ACM Trans. Graph. 43 4 (2024) 42:1\u201342:13.","DOI":"10.1145\/3658131"},{"key":"e_1_3_3_2_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/2485895.2485919"},{"key":"e_1_3_3_2_15_1","doi-asserted-by":"crossref","unstructured":"Michael\u00a0S. Floater. 2003. Mean value coordinates. Comput. Aided Geom. Des. 20 1 (2003) 19\u201327. https:\/\/doi.org\/10.1016\/S0167-8396(03)00002-5","DOI":"10.1016\/S0167-8396(03)00002-5"},{"key":"e_1_3_3_2_16_1","volume-title":"Forty-first International Conference on Machine Learning, ICML 2024, Vienna, Austria, July 21-27, 2024","author":"Gao Alexander","year":"2024","unstructured":"Alexander Gao, Maurice Chu, Mubbasir Kapadia, Ming\u00a0C. Lin, and Hsueh-Ti\u00a0Derek Liu. 2024. An Intrinsic Vector Heat Network. In Forty-first International Conference on Machine Learning, ICML 2024, Vienna, Austria, July 21-27, 2024. OpenReview.net."},{"key":"e_1_3_3_2_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/BigDIA60676.2023.10429306"},{"key":"e_1_3_3_2_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/258734.258849"},{"key":"e_1_3_3_2_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW.2019.00509"},{"key":"e_1_3_3_2_20_1","unstructured":"Jia-Peng Guo Wen-Xiang Zhang Chunyang Ye and Xiao-Ming Fu. 2023. Robust Coarse Cage Construction With Small Approximation Errors. IEEE Transactions on Visualization and Computer Graphics (2023)."},{"key":"e_1_3_3_2_21_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00072"},{"key":"e_1_3_3_2_22_1","doi-asserted-by":"crossref","unstructured":"Rana Hanocka Amir Hertz Noa Fish Raja Giryes Shachar Fleishman and Daniel Cohen-Or. 2019. MeshCNN: a network with an edge. ACM Trans. Graph. 38 4 (2019) 90:1\u201390:12.","DOI":"10.1145\/3306346.3322959"},{"key":"e_1_3_3_2_23_1","doi-asserted-by":"crossref","unstructured":"Amir Hertz Rana Hanocka Raja Giryes and Daniel Cohen-Or. 2020. Deep geometric texture synthesis. ACM Trans. Graph. 39 4 (2020) 108.","DOI":"10.1145\/3386569.3392471"},{"key":"e_1_3_3_2_24_1","doi-asserted-by":"crossref","unstructured":"Shi-Min Hu Zheng-Ning Liu Meng-Hao Guo Junxiong Cai Jiahui Huang Tai-Jiang Mu and Ralph\u00a0R. Martin. 2022. Subdivision-based Mesh Convolution Networks. ACM Trans. Graph. 41 3 (2022) 25:1\u201325:16.","DOI":"10.1145\/3506694"},{"key":"e_1_3_3_2_25_1","doi-asserted-by":"crossref","unstructured":"Yixin Hu Teseo Schneider Bolun Wang Denis Zorin and Daniele Panozzo. 2020. Fast tetrahedral meshing in the wild. ACM Trans. Graph. 39 4 (2020) 117.","DOI":"10.1145\/3386569.3392385"},{"key":"e_1_3_3_2_26_1","doi-asserted-by":"crossref","unstructured":"Yixin Hu Qingnan Zhou Xifeng Gao Alec Jacobson Denis Zorin and Daniele Panozzo. 2018. Tetrahedral Meshing in the Wild. ACM Trans. Graph. 37 4 Article 60 (July 2018) 14\u00a0pages. https:\/\/doi.org\/10.1145\/3197517.3201353","DOI":"10.1145\/3197517.3201353"},{"key":"e_1_3_3_2_27_1","unstructured":"Jiajun Huang and Hongchuan Yu. 2024. GSDeformer: Direct Cage-based Deformation for 3D Gaussian Splatting. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2405.15491 (2024)."},{"key":"e_1_3_3_2_28_1","unstructured":"Jingwei Huang Yichao Zhou and Leonidas\u00a0J. Guibas. 2020. ManifoldPlus: A Robust and Scalable Watertight Manifold Surface Generation Method for Triangle Soups. CoRR abs\/2005.11621 (2020). arXiv:https:\/\/arXiv.org\/abs\/2005.11621https:\/\/arxiv.org\/abs\/2005.11621"},{"key":"e_1_3_3_2_29_1","doi-asserted-by":"crossref","unstructured":"Alec Jacobson Ilya Baran Jovan Popovic and Olga Sorkine. 2011. Bounded biharmonic weights for real-time deformation. ACM Trans. Graph. 30 4 (2011) 78. https:\/\/doi.org\/10.1145\/2010324.1964973","DOI":"10.1145\/2010324.1964973"},{"key":"e_1_3_3_2_30_1","doi-asserted-by":"publisher","DOI":"10.1145\/2614028.2615427"},{"key":"e_1_3_3_2_31_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01259"},{"key":"e_1_3_3_2_32_1","doi-asserted-by":"crossref","unstructured":"Pushkar Joshi Mark Meyer Tony DeRose Brian Green and Tom Sanocki. 2007. Harmonic coordinates for character articulation. ACM Trans. Graph. 26 3 (2007) 71. https:\/\/doi.org\/10.1145\/1276377.1276466","DOI":"10.1145\/1276377.1276466"},{"key":"e_1_3_3_2_33_1","doi-asserted-by":"crossref","unstructured":"Tao Ju Qian-Yi Zhou Michiel Van De\u00a0Panne Daniel Cohen-Or and Ulrich Neumann. 2008. Reusable skinning templates using cage-based deformations. ACM Transactions on Graphics (ToG) 27 5 (2008) 1\u201310.","DOI":"10.1145\/1409060.1409075"},{"key":"e_1_3_3_2_34_1","doi-asserted-by":"crossref","unstructured":"Alon Lahav and Ayellet Tal. 2020. MeshWalker: deep mesh understanding by random walks. ACM Trans. Graph. 39 6 (2020) 263:1\u2013263:13.","DOI":"10.1145\/3414685.3417806"},{"key":"e_1_3_3_2_35_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-20062-5_3"},{"key":"e_1_3_3_2_36_1","series-title":"Lecture Notes in Computer Science","first-page":"349","volume-title":"Computer Vision - ECCV 2018 Workshops - Munich, Germany, September 8-14, 2018, Proceedings, Part III","volume":"11131","author":"Lim Isaak","year":"2018","unstructured":"Isaak Lim, Alexander Dielen, Marcel Campen, and Leif Kobbelt. 2018. A Simple Approach to Intrinsic Correspondence Learning on Unstructured 3D Meshes. In Computer Vision - ECCV 2018 Workshops - Munich, Germany, September 8-14, 2018, Proceedings, Part III(Lecture Notes in Computer Science, Vol.\u00a011131), Laura Leal-Taix\u00e9 and Stefan Roth (Eds.). Springer, 349\u2013362."},{"key":"e_1_3_3_2_37_1","doi-asserted-by":"crossref","unstructured":"Hsueh-Ti\u00a0Derek Liu Vladimir\u00a0G. Kim Siddhartha Chaudhuri Noam Aigerman and Alec Jacobson. 2020. Neural subdivision. ACM Trans. Graph. 39 4 (2020) 124.","DOI":"10.1145\/3386569.3392418"},{"key":"e_1_3_3_2_38_1","volume-title":"Blender Toolbox","author":"Liu Hsueh-Ti\u00a0Derek","year":"2018","unstructured":"Hsueh-Ti\u00a0Derek Liu. 2018. Blender Toolbox. https:\/\/github.com\/HTDerekLiu\/BlenderToolbox"},{"key":"e_1_3_3_2_39_1","doi-asserted-by":"crossref","unstructured":"Lijuan Liu Youyi Zheng Di Tang Yi Yuan Changjie Fan and Kun Zhou. 2019. Neuroskinning: Automatic skin binding for production characters with deep graph networks. ACM Transactions on Graphics (ToG) 38 4 (2019) 1\u201312.","DOI":"10.1145\/3306346.3322969"},{"key":"e_1_3_3_2_40_1","doi-asserted-by":"crossref","unstructured":"Jing Ma Jituo Li and Dongliang Zhang. 2024. EasySkinning: Target-oriented skinning by mesh contraction and curve editing. Comput. Graph. 124 (2024) 104049. https:\/\/doi.org\/10.1016\/J.CAG.2024.104049","DOI":"10.1016\/j.cag.2024.104049"},{"key":"e_1_3_3_2_41_1","doi-asserted-by":"crossref","unstructured":"Jing Ma and Dongliang Zhang. 2023. TARig: Adaptive template-aware neural rigging for humanoid characters. Comput. Graph. 114 (2023) 158\u2013167. https:\/\/doi.org\/10.1016\/J.CAG.2023.05.018","DOI":"10.1016\/j.cag.2023.05.018"},{"key":"e_1_3_3_2_42_1","doi-asserted-by":"crossref","unstructured":"Haggai Maron Meirav Galun Noam Aigerman Miri Trope Nadav Dym Ersin Yumer Vladimir\u00a0G. Kim and Yaron Lipman. 2017. Convolutional neural networks on surfaces via seamless toric covers. ACM Trans. Graph. 36 4 (2017) 71:1\u201371:10.","DOI":"10.1145\/3072959.3073616"},{"key":"e_1_3_3_2_43_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW.2015.112"},{"key":"e_1_3_3_2_44_1","volume-title":"Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020, December 6-12, 2020, virtual","author":"Milano Francesco","year":"2020","unstructured":"Francesco Milano, Antonio Loquercio, Antoni Rosinol, Davide Scaramuzza, and Luca Carlone. 2020. Primal-Dual Mesh Convolutional Neural Networks. In Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020, December 6-12, 2020, virtual, Hugo Larochelle, Marc\u2019Aurelio Ranzato, Raia Hadsell, Maria-Florina Balcan, and Hsuan-Tien Lin (Eds.)."},{"key":"e_1_3_3_2_45_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00985"},{"key":"e_1_3_3_2_46_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01804"},{"key":"e_1_3_3_2_47_1","doi-asserted-by":"publisher","DOI":"10.1088\/1742-6596\/1550\/3\/032163"},{"key":"e_1_3_3_2_48_1","doi-asserted-by":"crossref","unstructured":"Xiaoyu Pan Jiancong Huang Jiaming Mai He Wang Honglin Li Tongkui Su Wenjun Wang and Xiaogang Jin. 2021. HeterSkinNet: A Heterogeneous Network for Skin Weights Prediction. Proc. ACM Comput. Graph. Interact. Tech. 4 1 (2021) 10:1\u201310:19. https:\/\/doi.org\/10.1145\/3451262","DOI":"10.1145\/3451262"},{"key":"e_1_3_3_2_49_1","first-page":"8024","volume-title":"Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, NeurIPS 2019, December 8-14, 2019, Vancouver, BC, Canada","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 K\u00f6pf, Edward\u00a0Z. 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: Annual Conference on Neural Information Processing Systems 2019, NeurIPS 2019, December 8-14, 2019, Vancouver, BC, Canada, Hanna\u00a0M. Wallach, Hugo Larochelle, Alina Beygelzimer, Florence d\u2019Alch\u00e9-Buc, Emily\u00a0B. Fox, and Roman Garnett (Eds.). 8024\u20138035."},{"key":"e_1_3_3_2_50_1","doi-asserted-by":"crossref","unstructured":"Yicong Peng Yichao Yan Shengqi Liu Yuhao Cheng Shanyan Guan Bowen Pan Guangtao Zhai and Xiaokang Yang. 2022. Cagenerf: Cage-based neural radiance field for generalized 3d deformation and animation. Advances in Neural Information Processing Systems 35 (2022) 31402\u201331415.","DOI":"10.52202\/068431-2277"},{"key":"e_1_3_3_2_51_1","doi-asserted-by":"crossref","unstructured":"Adrien Poulenard and Maks Ovsjanikov. 2018. Multi-directional geodesic neural networks via equivariant convolution. ACM Transactions on Graphics (TOG) 37 6 (2018) 1\u201314.","DOI":"10.1145\/3272127.3275102"},{"key":"e_1_3_3_2_52_1","first-page":"652","volume-title":"Proceedings of the IEEE conference on computer vision and pattern recognition","author":"Qi Charles\u00a0R","year":"2017","unstructured":"Charles\u00a0R Qi, Hao Su, Kaichun Mo, and Leonidas\u00a0J Guibas. 2017. Pointnet: Deep learning on point sets for 3d classification and segmentation. In Proceedings of the IEEE conference on computer vision and pattern recognition. 652\u2013660."},{"key":"e_1_3_3_2_53_1","first-page":"599","volume-title":"Asian Conference on Computer Vision","author":"Savoye Yann","year":"2010","unstructured":"Yann Savoye and Jean-S\u00e9bastien Franco. 2010. Cage-based tracking for performance animation. In Asian Conference on Computer Vision. Springer, 599\u2013612."},{"key":"e_1_3_3_2_54_1","unstructured":"Silvia Sell\u00e1n Oded Stein et\u00a0al. 2023. gptyoolbox: A Python Geometry Processing Toolbox. https:\/\/gpytoolbox.org\/."},{"key":"e_1_3_3_2_55_1","doi-asserted-by":"crossref","unstructured":"Nicholas Sharp Souhaib Attaiki Keenan Crane and Maks Ovsjanikov. 2022. DiffusionNet: Discretization Agnostic Learning on Surfaces. ACM Trans. Graph. 41 3 (2022) 27:1\u201327:16.","DOI":"10.1145\/3507905"},{"key":"e_1_3_3_2_56_1","doi-asserted-by":"publisher","DOI":"10.1111\/cgf.14069"},{"key":"e_1_3_3_2_57_1","doi-asserted-by":"crossref","unstructured":"Dmitriy Smirnov and Justin Solomon. 2021. HodgeNet: learning spectral geometry on triangle meshes. ACM Trans. Graph. 40 4 (2021) 166:1\u2013166:11.","DOI":"10.1145\/3450626.3459797"},{"key":"e_1_3_3_2_58_1","doi-asserted-by":"publisher","DOI":"10.1111\/cgf.15060"},{"key":"e_1_3_3_2_59_1","doi-asserted-by":"crossref","unstructured":"Jean-Marc Thiery \u00c9lie Michel and Jiong Chen. 2024. Biharmonic Coordinates and their Derivatives for Triangular 3D Cages. ACM Trans. Graph. 43 4 (2024) 138:1\u2013138:17.","DOI":"10.1145\/3658208"},{"key":"e_1_3_3_2_60_1","doi-asserted-by":"crossref","unstructured":"Robert Tibshirani. 1996. Regression shrinkage and selection via the lasso. Journal of the Royal Statistical Society Series B: Statistical Methodology 58 1 (1996) 267\u2013288.","DOI":"10.1111\/j.2517-6161.1996.tb02080.x"},{"key":"e_1_3_3_2_61_1","doi-asserted-by":"crossref","unstructured":"Peng-Shuai Wang Yang Liu and Xin Tong. 2022. Dual octree graph networks for learning adaptive volumetric shape representations. ACM Trans. Graph. 41 4 (2022) 103:1\u2013103:15. https:\/\/doi.org\/10.1145\/3528223.3530087","DOI":"10.1145\/3528223.3530087"},{"key":"e_1_3_3_2_62_1","doi-asserted-by":"crossref","unstructured":"Yu Wang and Justin Solomon. 2021. Fast quasi-harmonic weights for geometric data interpolation. ACM Trans. Graph. 40 4 (2021) 73:1\u201373:15. https:\/\/doi.org\/10.1145\/3450626.3459801","DOI":"10.1145\/3450626.3459801"},{"key":"e_1_3_3_2_63_1","doi-asserted-by":"crossref","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.","DOI":"10.1145\/3326362"},{"key":"e_1_3_3_2_64_1","doi-asserted-by":"crossref","unstructured":"Ruben Wiersma Elmar Eisemann and Klaus Hildebrandt. 2020. CNNs on surfaces using rotation-equivariant features. ACM Transactions on Graphics (ToG) 39 4 (2020) 92\u20131.","DOI":"10.1145\/3386569.3392437"},{"key":"e_1_3_3_2_65_1","doi-asserted-by":"crossref","unstructured":"Jianfeng Xiang Zelong Lv Sicheng Xu Yu Deng Ruicheng Wang Bowen Zhang Dong Chen Xin Tong and Jiaolong Yang. 2024. Structured 3D Latents for Scalable and Versatile 3D Generation. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2412.01506 (2024).","DOI":"10.1109\/CVPR52734.2025.02000"},{"key":"e_1_3_3_2_66_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19827-4_10"},{"key":"e_1_3_3_2_67_1","doi-asserted-by":"crossref","unstructured":"Zhan Xu Yang Zhou Evangelos Kalogerakis Chris Landreth and Karan Singh. 2020. RigNet: neural rigging for articulated characters. ACM Trans. Graph. 39 4 (2020) 58. https:\/\/doi.org\/10.1145\/3386569.3392379","DOI":"10.1145\/3386569.3392379"},{"key":"e_1_3_3_2_68_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01359"},{"key":"e_1_3_3_2_69_1","doi-asserted-by":"publisher","DOI":"10.1109\/WACV48630.2021.00018"},{"key":"e_1_3_3_2_70_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00015"},{"key":"e_1_3_3_2_71_1","unstructured":"Shengchao Yuan Yishun Dou Rui Shi Bingbing Ni and Zhong Zheng. 2023. SieveNet: Selecting Point-Based Features for Mesh Networks. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2308.12530 (2023)."},{"key":"e_1_3_3_2_72_1","doi-asserted-by":"crossref","unstructured":"Cem Yuksel. 2015. Sample Elimination for Generating Poisson Disk Sample Sets. Computer Graphics Forum (Proceedings of EUROGRAPHICS 2015) 34 2 (2015) 25\u201332. https:\/\/doi.org\/10.1111\/cgf.12538","DOI":"10.1111\/cgf.12538"},{"key":"e_1_3_3_2_73_1","doi-asserted-by":"crossref","unstructured":"Kun Zhou Weiwei Xu Yiying Tong and Mathieu Desbrun. 2010. Deformation Transfer to Multi-Component Objects. Comput. Graph. Forum 29 2 (2010) 319\u2013325.","DOI":"10.1111\/j.1467-8659.2009.01601.x"},{"key":"e_1_3_3_2_74_1","unstructured":"Daniel Zint Zhouyuan Chen Yifei Zhu Denis Zorin Teseo Schneider and Daniele Panozzo. 2024. Topological Offsets. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2407.07725 (2024)."}],"event":{"name":"SIGGRAPH Conference Papers '25: Special Interest Group on Computer Graphics and Interactive Techniques Conference Conference Papers","location":"Vancouver BC Canada","acronym":"SIGGRAPH Conference Papers '25","sponsor":["SIGGRAPH ACM Special Interest Group on Computer Graphics and Interactive Techniques"]},"container-title":["Proceedings of the Special Interest Group on Computer Graphics and Interactive Techniques Conference Conference Papers"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3721238.3730654","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T14:52:09Z","timestamp":1774018329000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3721238.3730654"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7,27]]},"references-count":73,"alternative-id":["10.1145\/3721238.3730654","10.1145\/3721238"],"URL":"https:\/\/doi.org\/10.1145\/3721238.3730654","relation":{},"subject":[],"published":{"date-parts":[[2025,7,27]]},"assertion":[{"value":"2025-07-27","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}