NDLI: Category-wise feature extractor based on ADL method for weak-supervised object localisation

Content Provider	IET Digital Library
Author	Hu, Yanzhu Zhu, Dongdong Ai, Xinbo Xu, Yabo
Abstract	Fully supervised object detection needs to use the data set with object category annotation and location annotation to train the model. In contrast, weak supervised object localisation only needs to use the data set with object category annotation to train the model, but it can complete the classification task and object localisation task at the same time. Inspired by the attention-based dropout layer (ADL) method, this study designs a category-wise feature extractor (CFE), which can explicitly obtain the localisation map used to indicate the object location, and it is directly related to the category output of the classification task. Although its amount of calculation is slightly larger than that of the ADL method, the performance is better than ADL in some tasks. In addition to the standard CFE method mentioned above, this study also designs a lightweight CFE-tiny method, which adopts split-attention mechanism, and the calculation amount of this method is much smaller than that of ADL method.
Starting Page	3965
Ending Page	3974
Page Count	10
ISSN	17519659
Volume Number	14
e-ISSN	17519667
Issue Number	Issue 15, Dec (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/14/15
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2020.0640
Journal	IET Image Processing
Publisher Date	2020-12-04
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	ADL Method Attention-based Dropout Layer Method Category Output Category-wise Feature Extractor Classification Task Computer Vision And Image Processing Technique Feature Extraction Image Classification Image Recognition Learning in AI Lightweight CFE-tiny Method Localisation Map Localisation Task Location Annotation Object Category Annotation Object Detection Object Location Standard CFE Method Supervised Learning Supervised Object Detection Weak Supervised Object Localisation Weak-supervised Object Localisation
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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