Learning Flow-based Feature Warping for Face Frontalization with Illumination Inconsistent Supervision
european conference on computer vision, pp. 558-574, 2020.
Abstract:
Despite recent advances in deep learning-based face frontalization methods, photo-realistic and illumination preserving frontal face synthesis is still challenging due to large pose and illumination discrepancy during training. We propose a novel Flow-based Feature Warping Model (FFWM) which can learn to synthesize photo-realistic and i...More
Code:
Data:
Full Text
Tags
Comments