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This, however, comes with the lack of intuitive editability offered by traditional triangle mesh\u2010based methods. In contrast, we propose a method that combines the accuracy and fidelity of 2D Gaussian Splatting with the intuitiveness of UV texture mapping. By embedding each canonical Gaussian primitive's local frame into a patch in the UV space of a template mesh in a computationally efficient manner, we reconstruct continuous editable material head textures from a single monocular video on a conventional UV domain. Furthermore, we leverage an efficient physically based reflectance model to enable relighting and editing of these intrinsic material maps. Through extensive comparisons with state\u2010of\u2010the\u2010art methods, we demonstrate the accuracy of our reconstructions, the quality of our relighting results, and the ability to provide intuitive controls for modifying an avatar's appearance and geometry via texture mapping without additional optimization.<\/jats:p>","DOI":"10.1111\/cgf.70351","type":"journal-article","created":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T13:31:42Z","timestamp":1774618302000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["GTAvatar: Bridging Gaussian Splatting and Texture Mapping for Relightable and Editable Gaussian Avatars"],"prefix":"10.1111","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1732-4653","authenticated-orcid":false,"given":"Kelian","family":"Baert","sequence":"first","affiliation":[{"name":"Univ Rennes, Inria, CNRS, IRISA  France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4831-3343","authenticated-orcid":false,"given":"Mae","family":"Younes","sequence":"additional","affiliation":[{"name":"Univ Rennes, Inria, CNRS, IRISA  France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-3819-735X","authenticated-orcid":false,"given":"Francois","family":"Bourel","sequence":"additional","affiliation":[{"name":"Univ Rennes, Inria, CNRS, IRISA  France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6080-8026","authenticated-orcid":false,"given":"Marc","family":"Christie","sequence":"additional","affiliation":[{"name":"Univ Rennes, Inria, CNRS, IRISA  France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0529-7598","authenticated-orcid":false,"given":"Adnane","family":"Boukhayma","sequence":"additional","affiliation":[{"name":"Univ Rennes, Inria, CNRS, IRISA  France"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,3,27]]},"reference":[{"key":"e_1_2_8_2_2","doi-asserted-by":"crossref","unstructured":"Abrevaya Victoria Fern\u00e1ndez Boukhayma Adnane Wuhrer Stefanie andBoyer Edmond. \u201cA Decoupled 3D Facial Shape Model by Adversarial Training\u201d.Proceedings of the IEEE\/CVF International Conference on Computer Vision (ICCV). 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