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Zhizhi Guo

2 accepted papers

2022

Expressive Talking Head Generation With Granular Audio-Visual Control

CVPR 2022poster

Generating expressive talking heads is essential for creating virtual humans. However, existing one- or few-shot methods focus on lip-sync and head motion, ignoring the emotional expressions that make talking faces realistic. In this paper, we propose the Granularly Controlled Audio-Visual Talking H…

Cited by 148PDFScholar
2022

StyleSwap: Style-Based Generator Empowers Robust Face Swapping

ECCV 2022poster

"Numerous attempts have been made to the task of person-agnostic face swapping given its wide applications. While existing methods mostly rely on tedious network and loss designs, they still struggle in the information balancing between the source and target faces, and tend to produce visible artifa…