We present a system for the creation of realistic one-shot mesh-based (ROME) human head avatars. From a single photograph, our system estimates the head mesh (with person-specific details in both the facial and non-facial head parts) as well as the neural texture encoding, local photometric and geometric details. The resulting avatars are rigged and can be rendered using a deep rendering network, which is trained alongside the mesh and texture estimators on a dataset of in-the-wild videos. In the experiments, we observe that our system performs competitively both in terms of head geometry recovery and the quality of renders, especially for cross-person reenactment.
CITATION STYLE
Khakhulin, T., Sklyarova, V., Lempitsky, V., & Zakharov, E. (2022). Realistic One-Shot Mesh-Based Head Avatars. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 13662 LNCS, pp. 345–362). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-20086-1_20
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