Dense 3D Coordinate Code Prior Guidance for High-Fidelity Face Swapping and Face Reenactment

In face synthesis tasks, commonly used 2D face representations (e.g. 2D landmarks, segmentation maps, etc.) are usually sparse and discontinuous. To combat these shortcomings, we utilize a dense and continuous representation, named Projected Normalized Coordinate Code (PNCC), as the guidance and develop a PNCC-Spatio-Normalization (PSN) method to achieve face synthesis regarding arbitrary head poses and expressions. Based on PSN, we provide an effective framework for face reenactment and face swapping task. To ensure a harmonious and seamless face swapping, a simple yet effective Appearance-Blending Module (ABM) is proposed to fit the synthesized face to the target face. Our method is subject-agnostic and can be applied to any pair of faces without extra fine-tuning. Both qualitative and quantitative experiments are conducted to demonstrate the superiority of the proposed method in comparisons to existing state-of-the-art systems.