Institute of Computing Technology, Chinese Academy IR
Consensus-Agent Deep Reinforcement Learning for Face Aging | |
Lin, Ling1,2; Liu, Hao1,2; Liang, Jinqiao1,2; Li, Zhendong1,2; Feng, Jiao3; Han, Hu4,5 | |
2024 | |
发表期刊 | IEEE TRANSACTIONS ON IMAGE PROCESSING
![]() |
ISSN | 1057-7149 |
卷号 | 33页码:1795-1809 |
摘要 | Face aging tasks aim to simulate changes in the appearance of faces over time. However, due to the lack of data on different ages under the same identity, existing models are commonly trained using mapping between age groups. This makes it difficult for most existing aging methods to accurately capture the correspondence between individual identities and aging features, leading to generating faces that do not match the real aging appearance. In this paper, we re-annotate the CACD2000 dataset and propose a consensus-agent deep reinforcement learning method to solve the aforementioned problem. Specifically, we define two agents, the aging process agent and the aging personalization agent, and model the task of matching aging features as a Markov decision process. The aging process agent simulates the aging process of an individual, while the aging personalization agent calculates the difference between the aging appearance of an individual and the average aging appearance. The two agents iteratively adjust the matching degree between the target aging feature and the current identity through a form of synergistic cooperation. Extensive experimental results on four face aging datasets show that our model achieves convincing performance compared to the current state-of-the-art methods. |
关键词 | Face aging deep reinforcement learning Markov decision process |
DOI | 10.1109/TIP.2024.3364074 |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Natural Science Foundation of China |
WOS研究方向 | Computer Science ; Engineering |
WOS类目 | Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic |
WOS记录号 | WOS:001184885100006 |
出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.204/handle/2XEOYT63/38741 |
专题 | 中国科学院计算技术研究所期刊论文_英文 |
通讯作者 | Liu, Hao |
作者单位 | 1.Ningxia Univ, Sch Informat Engn, Yinchuan 750021, Peoples R China 2.Ningxia Key Lab Artificial Intelligence & Informat, Yinchuan 750021, Peoples R China 3.Ningxia Univ, Sch Innovat & Entrepreneurship, Yinchuan 750021, Peoples R China 4.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing 100190, Peoples R China 5.Univ Chinese Acad Sci, Beijing 100049, Peoples R China |
推荐引用方式 GB/T 7714 | Lin, Ling,Liu, Hao,Liang, Jinqiao,et al. Consensus-Agent Deep Reinforcement Learning for Face Aging[J]. IEEE TRANSACTIONS ON IMAGE PROCESSING,2024,33:1795-1809. |
APA | Lin, Ling,Liu, Hao,Liang, Jinqiao,Li, Zhendong,Feng, Jiao,&Han, Hu.(2024).Consensus-Agent Deep Reinforcement Learning for Face Aging.IEEE TRANSACTIONS ON IMAGE PROCESSING,33,1795-1809. |
MLA | Lin, Ling,et al."Consensus-Agent Deep Reinforcement Learning for Face Aging".IEEE TRANSACTIONS ON IMAGE PROCESSING 33(2024):1795-1809. |
条目包含的文件 | 条目无相关文件。 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论