Local Consistency Guidance: Personalized Stylization Method of Face Video (Student Abstract) - Feng, Wancheng; Liu, Yingchao; Pei, Jiaming; Liu, Wenxuan; Tian, Chunpeng; Wang, Lukun (Proceedings of the AAAI Conference on Artificial Intelligence, 2024)
Face video stylization aims to convert real face videos into specified reference styles. While one-shot methods perform well in single-image stylization, ensuring continuity between frames and retaining the original facial expressions present challenges in video stylization. To address these issues, our approach employs a personalized diffusion model with pixel-level control. We propose Local Consistency Guidance(LCG) strategy, composed of local-cross attention and local style transfer, to ensure temporal consistency. This framework enables the synthesis of high-quality stylized face videos with excellent temporal continuity.