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2 Result(s)

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  1. No Access

    Chapter and Conference Paper

    A Detail Geometry Learning Network for High-Fidelity Face Reconstruction

    In this paper, we propose a Detail Geometry Learning Network (DGLN) approach to investigate the problem of self-supervised high-fidelity face reconstruction from monocular images. Unlike existing methods that ...

    Kehua Ma, **tie Zhang, Su** Wu… in Artificial Neural Networks and Machine Lea… (2023)

  2. No Access

    Chapter and Conference Paper

    Unsupervised Shape Enhancement and Factorization Machine Network for 3D Face Reconstruction

    Existing unsupervised methods are often unable to capture accurate 3D shapes due to the ambiguity of shapes and albedo maps, limiting their applicability to downstream tasks. Therefore, this article proposes a...

    Leyang Yang, Boyang Zhang, Jianchang Gong… in Artificial Neural Networks and Machine Lea… (2023)