BEVCon: Advancing Bird's Eye View Perception with Contrastive Learning

We present BEVCon, a simple yet effective contrastive learning framework designed to improve Bird's Eye View (BEV) perception in autonomous driving. BEV perception offers a top-down-view representation of the surrounding environment, making it crucial for 3D object detection, segmentation, and...

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Bibliographische Detailangaben
Veröffentlicht in:	IEEE robotics and automation letters Jg. 10; H. 4; S. 1 - 7
Hauptverfasser:	Leng, Ziyang, Yang, Jiawei, Ren, Zhicheng, Zhou, Bolei
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 01.04.2025 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	and Categorization Annotations Autonomous vehicles Coders Contrastive learning Deep Learning for Visual Perception Feature extraction Head Learning Modules Object detection Object recognition Perception Representation learning Representations Segmentation Three-dimensional displays Training Transforms
ISSN:	2377-3766, 2377-3766
Online-Zugang:	Volltext
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