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High-fidelity and efficient audio-driven talking head generation has been akey research topic in computer graphics and computer vision. In this work, westudy vector image based audio-driven talking head generation. Compared withdirectly animating the raster image that most widely used in existing works,vector image enjoys its excellent scalability being used for many applications.There are two main challenges for vector image based talking head generation:the high-quality vector image reconstruction w.r.t. the source portrait imageand the vivid animation w.r.t. the audio signal. To address these, we propose anovel scalable vector graphic reconstruction and animation method, dubbedVectorTalker. Specifically, for the highfidelity reconstruction, VectorTalkerhierarchically reconstructs the vector image in a coarse-to-fine manner. Forthe vivid audio-driven facial animation, we propose to use facial landmarks asintermediate motion representation and propose an efficient landmark-drivenvector image deformation module. Our approach can handle various styles ofportrait images within a unified framework, including Japanese manga, cartoon,and photorealistic images. We conduct extensive quantitative and qualitativeevaluations and the experimental results demonstrate the superiority ofVectorTalker in both vector graphic reconstruction and audio-driven animation.

VectorTalker: SVG Talking Face Generation with Progressive Vectorisation