中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Parsing Objects at a Finer Granularity: A Survey

文献类型:期刊论文

作者Yifan Zhao1; Jia Li2; Yonghong Tian1
刊名Machine Intelligence Research
出版日期2024
卷号21期号:3页码:431-451
关键词Finer granularity, visual parsing, part segmentation, fine-grained object recognition, part relationship
ISSN号2731-538X
DOI10.1007/s11633-022-1404-6
英文摘要Fine-grained visual parsing, including fine-grained part segmentation and fine-grained object recognition, has attracted considerable critical attention due to its importance in many real-world applications, e.g., agriculture, remote sensing, and space technologies. Predominant research efforts tackle these fine-grained sub-tasks following different paradigms, while the inherent relations between these tasks are neglected. Moreover, given most of the research remains fragmented, we conduct an in-depth study of the advanced work from a new perspective of learning the part relationship. In this perspective, we first consolidate recent research and benchmark syntheses with new taxonomies. Based on this consolidation, we revisit the universal challenges in fine-grained part segmentation and recognition tasks and propose new solutions by part relationship learning for these important challenges. Furthermore, we conclude several promising lines of research in fine-grained visual parsing for future research.
源URL[http://ir.ia.ac.cn/handle/173211/56475]  
专题自动化研究所_学术期刊_International Journal of Automation and Computing
作者单位1.School of Computer Science, Peking University, Beijing 100871, China
2.State Key Laboratory of Virtual Reality Technology and Systems, School of Computer Science and Engineering, Beihang University, Beijing 100191, China
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Yifan Zhao,Jia Li,Yonghong Tian. Parsing Objects at a Finer Granularity: A Survey[J]. Machine Intelligence Research,2024,21(3):431-451.
APA Yifan Zhao,Jia Li,&Yonghong Tian.(2024).Parsing Objects at a Finer Granularity: A Survey.Machine Intelligence Research,21(3),431-451.
MLA Yifan Zhao,et al."Parsing Objects at a Finer Granularity: A Survey".Machine Intelligence Research 21.3(2024):431-451.

入库方式: OAI收割

来源:自动化研究所

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