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We propose Self-supervised Motion Fields (SMF), a self-supervised framework that is trained with only sparse motion representations, without requiring dataset-specific annotations, templates, or rigs. At the heart of our method are Kinetic Codes, a novel autoencoder-based sparse motion encoding, that exposes a semantically rich latent space, simplifying large-scale training. Our architecture comprises dedicated spatial and temporal gradient predictors, which are jointly trained in an end-to-end fashion. The combined network, regularized by the Kinetic Codes' latent space, has good generalization across both unseen shapes and new motions. We evaluated our method on unseen motion sampled from AMASS, D4D, Mixamo, and raw monocular video for animation transfer on various characters with varying shapes and topology. We report a new SoTA on the AMASS dataset in the context of generalization to unseen motion.<\/jats:p>","DOI":"10.1145\/3763309","type":"journal-article","created":{"date-parts":[[2025,12,4]],"date-time":"2025-12-04T17:15:39Z","timestamp":1764868539000},"page":"1-11","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["SMF: Template-free and Rig-free Animation Transfer using Kinetic Codes"],"prefix":"10.1145","volume":"44","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3556-5007","authenticated-orcid":false,"given":"Sanjeev","family":"Muralikrishnan","sequence":"first","affiliation":[{"name":"University College London (UCL), London, United Kingdom"},{"name":"Dolby Laboratories, Bengaluru, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7423-2221","authenticated-orcid":false,"given":"Niladri Shekhar","family":"Dutt","sequence":"additional","affiliation":[{"name":"University College London (UCL), London, United Kingdom"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2597-0914","authenticated-orcid":false,"given":"Niloy J.","family":"Mitra","sequence":"additional","affiliation":[{"name":"University College London (UCL), London, United Kingdom"},{"name":"Adobe Research, London, United Kingdom"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2025,12,4]]},"reference":[{"key":"e_1_2_2_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/3450626.3459769"},{"key":"e_1_2_2_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/3386569.3392462"},{"key":"e_1_2_2_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/3528223.3530141"},{"key":"e_1_2_2_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW.2011.6130444"},{"key":"e_1_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/1276377.1276467"},{"key":"e_1_2_2_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.491"},{"key":"e_1_2_2_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/74334.74358"},{"key":"e_1_2_2_8_1","volume-title":"Augmented neural odes. 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