Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Jonathan Hans Soeseno"'
Publikováno v:
IEEE Access, Vol 7, Pp 36400-36412 (2019)
There are many existing models that are capable of changing hair color or changing facial expressions. These models are typically implemented as deep neural networks that require a large number of computations in order to perform the transformations.
Externí odkaz:
https://doaj.org/article/b6e6260f9168483990256f0abb61160b
Publikováno v:
IEEE Transactions on Cybernetics, 52(6), 4825-4836. IEEE Advancing Technology for Humanity
Tan, D S, Soeseno, J H & Hua, K-L 2022, ' Controllable and Identity-Aware Facial Attribute Transformation ', IEEE Transactions on Cybernetics, vol. 52, no. 6, pp. 4825-4836 . https://doi.org/10.1109/TCYB.2021.3071172
Tan, D S, Soeseno, J H & Hua, K-L 2022, ' Controllable and Identity-Aware Facial Attribute Transformation ', IEEE Transactions on Cybernetics, vol. 52, no. 6, pp. 4825-4836 . https://doi.org/10.1109/TCYB.2021.3071172
Modifying facial attributes without the paired dataset proves to be a challenging task. Previously, approaches either required supervision from a ground-truth transformed image or required training a separate model for mapping every pair of attribute
Autor:
Trista Pei-Chun Chen, Lin Shih-Sung, Yi-Chun Chen, Bo-Huei He, Jonathan Hans Soeseno, Wei-Chao Chen, Daniel Stanley Tan
Publikováno v:
APSIPA Transactions on Signal and Information Processing. 10
In this article, we discuss the backgrounds and technical details about several smart manufacturing projects in a tier-one electronics manufacturing facility. We devise a process to manage logistic forecast and inventory preparation for electronic pa
Motion synthesis in a dynamic environment has been a long-standing problem for character animation. Methods using motion capture data tend to scale poorly in complex environments because of their larger capturing and labeling requirement. Physics-bas
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f4fe3da3ca4aa59ac91d2151bab25b46
http://arxiv.org/abs/2005.03288
http://arxiv.org/abs/2005.03288
Autor:
Jonathan Hans Soeseno
107
Modifying facial attributes without paired dataset proves to be a challenging task. Previous approaches either require supervision from a ground truth transformed image or require training a separate model for mapping every pair of attribute
Modifying facial attributes without paired dataset proves to be a challenging task. Previous approaches either require supervision from a ground truth transformed image or require training a separate model for mapping every pair of attribute
Externí odkaz:
http://ndltd.ncl.edu.tw/handle/57qb5k
Publikováno v:
Scientific Data; 3/21/2023, Vol. 10 Issue 1, p1-16, 16p
Publikováno v:
ACM Transactions on Graphics; Dec2022, Vol. 41 Issue 6, p1-13, 13p
Publikováno v:
ACM Transactions on Graphics; Aug2022, Vol. 41 Issue 4, p1-17, 17p
Publikováno v:
ACM Transactions on Graphics; Jul2020, Vol. 39 Issue 4, p38:1-38:10, 1p