"Modeling digital human at high-fidelity has become key in many applications such as gaming, visual effects or virtual reality. To push further realism of human faces, we introduce a first data-driven generative model of eyelashes based on physical and semantic features. This model is derived from real data by introducing a new 3D hair reconstruction method from multi-view images. Thanks to an original dedicated extraction process, we determine the physical features of any given set of eyelashes, and present the most detailed and comprehensive statistical analysis of human eyelashes shape ever made. Compared to existing hair reconstruction techniques we show that our approach obtains much better result to reconstruct eyelashes. We show that this eyelashes model is also fully adapted to synthetic data generation. Results show that the proposed model enables interactive, intuitive and realistic eyelashes modeling for non experts, pushing the limits of avatar creation and synthetic data generation pipelines."
3D Reconstruction and Semantic Modeling of Eyelashes
3D Reconstruction and Semantic Modeling of Eyelashes
3D Reconstruction and Semantic Modeling of Eyelashes
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