Unsupervised Domain Adaptation with Multimodal Fusion for Monocular 3D Object Detection

This paper presents UM3D, an end-to-end unsupervised domain adaptation framework for monocular 3D object detection. Monocular 3D object detection is appealing due to its low cost, yet it suffers from limited depth cues and poor cross-domain generalization when labeled data are scarce. Existing Pseud...

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Autors principals:	Jin Jiang, Jidong Dai, Wei Li, Yuquan Zhou, Maozhang Ye, Jianhuan Zhang, Chentao Zhang
Format:	Artigo
Idioma:	Inglês
Publicat:	MDPI AG 2026-05-01
Col·lecció:	Vehicles
Matèries:	monocular 3D object detection unsupervised domain adaptation Pseudo-LiDAR multimodal fusion
Accés en línia:	https://www.mdpi.com/2624-8921/8/5/98
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