Learning an interpretable stylized subspace for 3D-aware animatable artforms

• Main Authors: ZHENG, Chenxi, LIU, Bangzhen, XU, Xuemiao, ZHANG, Huaidong, HE, Shengfeng
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2024
• Subjects: 3D-aware GANs; Adaptation models; facial attribute editing; Image reconstruction; Painting; stylized animation; Three-dimensional displays; Training; Graphics and Human Computer Interfaces; Software Engineering
• 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
• Institution: Singapore Management University

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...