Accurate 3D Face Reconstruction with Weakly-Supervised Learning: From Single Image to Image Set

20 Mar 2019Yu DengJiaolong YangSicheng XuDong ChenYunde JiaXin Tong

Recently, deep learning based 3D face reconstruction methods have shown promising results in both quality and efficiency.However, training deep neural networks typically requires a large volume of data, whereas face images with ground-truth 3D face shapes are scarce. In this paper, we propose a novel deep 3D face reconstruction approach that 1) leverages a robust, hybrid loss function for weakly-supervised learning which takes into account both low-level and perception-level information for supervision, and 2) performs multi-image face reconstruction by exploiting complementary information from different images for shape aggregation... (read more)

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