Weakly Supervised Object Localization with Background Suppression Erasing for Art Authentication and Copyright Protection
Chaojie Wu1
刊名Machine Intelligence Research
2024
卷号21期号:1页码:89-103
关键词Weakly supervised object localization, erasing method, deep learning, computer vision, art authentication and copyright protection
ISSN号2731-538X
DOI10.1007/s11633-023-1455-3
英文摘要The problem of art forgery and infringement is becoming increasingly prominent, since diverse self-media contents with all kinds of art pieces are released on the Internet every day. For art paintings, object detection and localization provide an efficient and effective means of art authentication and copyright protection. However, the acquisition of a precise detector requires large amounts of expensive pixel-level annotations. To alleviate this, we propose a novel weakly supervised object localization (WSOL) with background superposition erasing (BSE), which recognizes objects with inexpensive image-level labels. First, integrated adversarial erasing (IAE) for vanilla convolutional neural network (CNN) dropouts the most discriminative region by leveraging high-level semantic information. Second, a background suppression module (BSM) limits the activation area of the IAE to the object region through a self-guidance mechanism. Finally, in the inference phase, we utilize the refined importance map (RIM) of middle features to obtain class-agnostic localization results. Extensive experiments are conducted on paintings, CUB-200-2011 and ILSVRC to validate the effectiveness of our BSE.
内容类型期刊论文
源URL[http://ir.ia.ac.cn/handle/173211/54577]  
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 and Engineering, South China University of Technology, Guangzhou 511442, China
2.Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangdong Provincial People′s Hospital, Guangzhou 510180, China
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GB/T 7714
Chaojie Wu. Weakly Supervised Object Localization with Background Suppression Erasing for Art Authentication and Copyright Protection[J]. Machine Intelligence Research,2024,21(1):89-103.
APA Chaojie Wu.(2024).Weakly Supervised Object Localization with Background Suppression Erasing for Art Authentication and Copyright Protection.Machine Intelligence Research,21(1),89-103.
MLA Chaojie Wu."Weakly Supervised Object Localization with Background Suppression Erasing for Art Authentication and Copyright Protection".Machine Intelligence Research 21.1(2024):89-103.
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