Learning an interpretable stylized subspace for 3D-aware animatable artforms
Throughout history, static paintings have captivated viewers within display frames, yet the possibility of making these masterpieces vividly interactive remains intriguing. This research paper introduces 3DArtmator, a novel approach that aims to represent artforms in a highly interpretable stylized...
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Main Authors: | ZHENG, Chenxi, LIU, Bangzhen, XU, Xuemiao, ZHANG, Huaidong, HE, Shengfeng |
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Format: | text |
Language: | English |
Published: |
Institutional Knowledge at Singapore Management University
2024
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Online Access: | https://ink.library.smu.edu.sg/sis_research/8697 https://ink.library.smu.edu.sg/context/sis_research/article/9700/viewcontent/LearningInterpretableStylizedAnimatable_Artforms_av.pdf |
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Institution: | Singapore Management University |
Language: | English |
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