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231225s2023 xx |||||o 00| ||eng c |
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|a 10.1109/TVCG.2021.3117484
|2 doi
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|a pubmed24n1104.xml
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|a DE-627
|b ger
|c DE-627
|e rakwb
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| 041 |
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|a eng
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| 100 |
1 |
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|a Zhang, Chenxu
|e verfasserin
|4 aut
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| 245 |
1 |
0 |
|a 3D Talking Face With Personalized Pose Dynamics
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| 264 |
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|c 2023
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| 336 |
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|a Text
|b txt
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|a ƒaComputermedien
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|a ƒa Online-Ressource
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|2 rdacarrier
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| 500 |
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|a Date Completed 06.04.2023
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| 500 |
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|a Date Revised 03.05.2023
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|a published: Print-Electronic
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|a Citation Status MEDLINE
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| 520 |
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|a Recently, we have witnessed a boom in applications for 3D talking face generation. However, most existing 3D face generation methods can only generate 3D faces with a static head pose, which is inconsistent with how humans perceive faces. Only a few articles focus on head pose generation, but even these ignore the attribute of personality. In this article, we propose a unified audio-driven approach to endow 3D talking faces with personalized pose dynamics. To achieve this goal, we establish an original person-specific dataset, providing corresponding head poses and face shapes for each video. Our framework is composed of two separate modules: PoseGAN and PGFace. Given an input audio, PoseGAN first produces a head pose sequence for the 3D head, and then, PGFace utilizes the audio and pose information to generate natural face models. With the combination of these two parts, a 3D talking head with dynamic head movement can be constructed. Experimental evidence indicates that our method can generate person-specific head pose sequences that are in sync with the input audio and that best match with the human experience of talking heads
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| 650 |
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|a Journal Article
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| 650 |
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4 |
|a Research Support, U.S. Gov't, Non-P.H.S.
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| 650 |
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4 |
|a Research Support, Non-U.S. Gov't
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| 700 |
1 |
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|a Ni, Saifeng
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Fan, Zhipeng
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Li, Hongbo
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Zeng, Ming
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Budagavi, Madhukar
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Guo, Xiaohu
|e verfasserin
|4 aut
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| 773 |
0 |
8 |
|i Enthalten in
|t IEEE transactions on visualization and computer graphics
|d 1996
|g 29(2023), 2 vom: 04. Feb., Seite 1438-1449
|w (DE-627)NLM098269445
|x 1941-0506
|7 nnns
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| 773 |
1 |
8 |
|g volume:29
|g year:2023
|g number:2
|g day:04
|g month:02
|g pages:1438-1449
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| 856 |
4 |
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|u http://dx.doi.org/10.1109/TVCG.2021.3117484
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