Diverse Feature-Level Guidance Adjustments for Unsupervised Domain Adaptative Object Detection

Diverse Feature-Level Guidance Adjustments for Unsupervised Domain Adaptative Object Detection

<b>Unsupervised Domain Adaptative Object Detection</b> (UDAOD) aims to alleviate the gap between the source domain and the target domain. Previous methods sought to plainly align global and local features across domains but adapted numerous pooled features and overlooked contextual infor...

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Bibliographic Details
Main Authors:	Yuhe Zhu, Chang Liu, Yunfei Bai, Caiju Wang, Chengwei Wei, Zhenglin Li, Yang Zhou
Format:	Article
Language:	English
Published:	MDPI AG 2024-03-01
Series:	Applied Sciences
Subjects:	unsupervised domain adaptative object detection feature distribution feature alignment foreground–background sample division
Online Access:	https://www.mdpi.com/2076-3417/14/7/2844

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