属性知识引导的自适应视觉感知与结构理解研究进展

doi:10.16451/j.cnki.issn1003-6059.202312004

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Abstract

Machines extract human-understandable information from the environment via adaptive perception to build intelligent system in open-world scenarios. Derived from the class-agnostic characteristics of attribute knowledge, attribution-guided perception methods and models are established and widely studied. In this paper, the tasks involved in attribution-guided adaptive visual perception and structure understanding are firstly introduced, and their applicable scenarios are analyzed. The representative research on four key aspects is summarized. Basic visual attribute knowledge extraction methods cover low-level geometric attributes and high-level cognitive attributes. Attribute knowledge-guided weakly-supervised visual perception includes weakly supervised learning and unsupervised learning under data label restrictions. Image self-supervised learning covers self-supervise contrastive learning and unsupervised commonality learning. Structured representation and understanding of scene images and their applications are introduced as well. Finally, challenges and potential research directions are discussed, such as the construction of large-scale benchmark datasets with multiple attributes, multi-modal attribute knowledge extraction, scene generalization of attribute knowledge perception models, the development of lightweight attribute knowledge-guided models and the practical applications of scene image representation.

Key words： Adaptive Perception Structure Understanding Attribution Knowledge Weakly-Supervised Learning Unsupervised Learning

Received: 07 October 2023

ZTFLH:

TP 37

Fund:

Supported by National Key Research and Development Program of China(No.2018AAA0100400), Natural Science Foundation for Distinguished Young Scholars of Tianjin(No.20JCJQJC00020), National Natural Science Foundation of China(No.62325109,U21B2013), Fundamental Research Funds for the Central Universities

Corresponding Authors: YANG Jufeng, Ph.D., professor. His research interests include computer vision.

About author:: ZHANG Zhicheng, Ph.D. candidate. His research interests include computer vision.
CHENG Mingming, Ph.D., professor. His research interests include computer vision.
LIN Weiyao, Ph.D., professor. His research interests include computer vision.

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Cite this article:

ZHANG Zhicheng,YANG Jufeng,CHENG Mingming等. Progress in Attribution-Guided Adaptive Visual Perception and Structure Understanding[J]. Pattern Recognition and Artificial Intelligence, 2023, 36(12): 1104-1126.

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http://manu46.magtech.com.cn/Jweb_prai/EN/10.16451/j.cnki.issn1003-6059.202312004 OR http://manu46.magtech.com.cn/Jweb_prai/EN/Y2023/V36/I12/1104

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