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We demonstrate our solution in a monocular video setting and an end-to-end VR telepresence system for two-way communication. Compared to 2D head reenactment methods, 3D-aware approaches aim to preserve the identity of the subject and ensure view-consistent facial geometry for novel camera poses, which makes them suitable for immersive applications. While various facial disentanglement techniques have been introduced, cutting-edge 3D-aware neural reenactment techniques still lack expressiveness and fail to reproduce complex and fine-scale facial expressions. We present a novel cross-reenactment architecture that directly transfers the driver's facial expressions to transformer blocks of the input source's 3D lifting module. We show that highly effective disentanglement is possible using a new multi-stage self-supervision approach. It relies on a coarse-to-fine training strategy, which is combined with explicit face neutralization and 3D lifted frontalization during its initial training stage. We further integrate our novel head reenactment solution into an accessible high-fidelity VR telepresence system, where any person can instantly build a personalized neural head avatar from any photo and bring it to life using the headset. Furthermore, our proposed method demonstrates state-of-the-art expressiveness and likeness preservation on diverse subjects and capture conditions.<\/jats:p>","DOI":"10.1145\/3687974","type":"journal-article","created":{"date-parts":[[2024,11,19]],"date-time":"2024-11-19T15:46:04Z","timestamp":1732031164000},"page":"1-26","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":11,"title":["VOODOO XP: Expressive One-Shot Head Reenactment for VR Telepresence"],"prefix":"10.1145","volume":"43","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-0865-6651","authenticated-orcid":false,"given":"Phong","family":"Tran","sequence":"first","affiliation":[{"name":"MBZUAI, Masdar City, United Arab Emirates"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9880-9531","authenticated-orcid":false,"given":"Egor","family":"Zakharov","sequence":"additional","affiliation":[{"name":"ETH Zurich, Zurich, Switzerland"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-5911-8945","authenticated-orcid":false,"given":"Long-Nhat","family":"Ho","sequence":"additional","affiliation":[{"name":"MBZUAI, Masdar City, United Arab Emirates"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-4923-5309","authenticated-orcid":false,"given":"Adilbek","family":"Karmanov","sequence":"additional","affiliation":[{"name":"MBZUAI, Masdar City, United Arab Emirates"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2826-7666","authenticated-orcid":false,"given":"Ariana","family":"Bermudez Venegas","sequence":"additional","affiliation":[{"name":"MBZUAI, Masdar City, United Arab Emirates"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0471-3860","authenticated-orcid":false,"given":"McLean","family":"Goldwhite","sequence":"additional","affiliation":[{"name":"Pinscreen, South Pasadena, United States of America"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-4787-7205","authenticated-orcid":false,"given":"Aviral","family":"Agarwal","sequence":"additional","affiliation":[{"name":"Pinscreen, IMPZ Production City, United Arab Emirates"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6614-5785","authenticated-orcid":false,"given":"Liwen","family":"Hu","sequence":"additional","affiliation":[{"name":"Pinscreen, Los Angeles, United States of America"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3120-4036","authenticated-orcid":false,"given":"Anh","family":"Tran","sequence":"additional","affiliation":[{"name":"VinAI Research, Hanoi, Vietnam"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4019-3420","authenticated-orcid":false,"given":"Hao","family":"Li","sequence":"additional","affiliation":[{"name":"MBZUAI, Masdar City, United Arab Emirates"},{"name":"Pinscreen, Los Angeles, USA"}]}],"member":"320","published-online":{"date-parts":[[2024,11,19]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR).","author":"An Sizhe","year":"2023","unstructured":"Sizhe An, Hongyi Xu, Yichun Shi, Guoxian Song, Umit Y. 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