中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
首页 机构 成果 学者
  
  1. CAS IR Grid
  2. 计算技术研究所
  3. 中国科学院计算技术研究所
  4. 中国科学院计算技术研究所期刊论文
  5. 英文
Consensus-Agent Deep Reinforcement Learning for Face Aging

文献类型：期刊论文

作者Lin, Ling4,5; Liu, Hao4,5; Liang, Jinqiao4,5; Li, Zhendong4,5; Feng, Jiao3; Han, Hu1,2
刊名IEEE TRANSACTIONS ON IMAGE PROCESSING
出版日期2024
卷号33页码:1795-1809
关键词Face aging deep reinforcement learning Markov decision process
ISSN号1057-7149
DOI10.1109/TIP.2024.3364074
英文摘要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.
资助项目National Natural Science Foundation of China
WOS研究方向Computer Science ; Engineering
语种英语
WOS记录号WOS:001184885100006
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
源URL[http://119.78.100.204/handle/2XEOYT63/38740]  
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.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
2.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing 100190, Peoples R China
3.Ningxia Univ, Sch Innovat & Entrepreneurship, Yinchuan 750021, Peoples R China
4.Ningxia Key Lab Artificial Intelligence & Informat, Yinchuan 750021, Peoples R China
5.Ningxia Univ, Sch Informat Engn, Yinchuan 750021, 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.

入库方式： OAI收割

来源：计算技术研究所

浏览0
下载0
收藏0
其他版本

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。