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Person-generic audio-driven face generation is a challenging task in computer vision.
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Zhang, Z., Li, L., Ding, Y., Fan, C.: Flow-guided one-shot talking face generation with a high-resolution audio-visual dataset. IEEE (2021)
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Cheng, K., Cun, X., Zhang, Y., Xia, M., Yin, F., Zhu, M., Wang, X., Wang, J., Wang, N.: Videoretalking: Audio-based lip synchronization for talking head video editing in the wild. In: SIGGRAPH Asia 2022 Conference Papers. pp. 1–9 (2022)
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Wang, J., Qian, X., Zhang, M., Tan, R.T., Li, H.: Seeing what you said: Talking face generation guided by a lip reading expert. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 14653–14662 (2023)
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Xu, C., Zhu, J., Zhang, J., Han, Y., Chu, W., Tai, Y., Wang, C., Xie, Z., Liu, Y.: High-fidelity generalized emotional talking face generation with multi-modal emotion space learning. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (2023)
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