Scale-Consistent and Temporally Ensembled Unsupervised Domain Adaptation for Object Detection

Scale-Consistent and Temporally Ensembled Unsupervised Domain Adaptation for Object Detection

Unsupervised Domain Adaptation for Object Detection (UDA-OD) aims to adapt a model trained on a labeled source domain to an unlabeled target domain, addressing challenges posed by domain shifts. However, existing methods often face significant challenges, particularly in detecting small objects and...

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Bibliographic Details
Main Authors: Lunfeng Guo, Yizhe Zhang, Jiayin Liu, Huajie Liu, Yunwang Li
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Sensors
Subjects:
object detection
autonomous driving
unsupervised domain adaption
Online Access:https://www.mdpi.com/1424-8220/25/1/230
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