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政大機構典藏 > 資訊學院 > 資訊科學系 > 會議論文 > Item 140.119/148299

Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/148299

Title:	Audio-driven facial landmark generation in violin performance using 3DCNN network with self attention model
Authors:	劉昭麟 Liu, Chao-Lin;Lin, Ting-Wei;Su, Li
Contributors:	資訊系
Keywords:	music to face generation;facial landmarks generation;music-face dataset;3DCNN;self-attention
Date:	2023-06
Issue Date:	2023-11-30 11:26:28 (UTC+8)
Abstract:	In a music scenario, both auditory and visual elements are essential to achieve an outstanding performance. Recent research has focused on the generation of body movements or fingering from audio in music performance. The audio-driven face generation technique in music performance is still deficient. In this paper, we compile a violin soundtrack and facial expression dataset (VSFE) for modeling facial expressions in violin performance. To our knowledge, this is the first dataset mapping the relationship between violin performance audio and musicians’ facial expressions. We then propose a 3DCNN network with self-attention and residual blocks for audio-driven facial expression generation. In the experiments, we compare our methods with three baselines on talking face generation.
Relation:	Proceedings of the 2023 IEEE International Conference on Acoustics, Speech and Signal Processing, IEEE, pp.1-5
Data Type:	conference
DOI 連結:	https://doi.org/10.1109/ICASSP49357.2023.10096358
DOI:	10.1109/ICASSP49357.2023.10096358
Appears in Collections:	[資訊科學系] 會議論文

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