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MOSE: Boosting Vision-based Roadside 3D Object Detection with Scene Cues
April 9, 2024, 4:47 a.m. | Xiahan Chen, Mingjian Chen, Sanli Tang, Yi Niu, Jiang Zhu
cs.CV updates on arXiv.org arxiv.org
Abstract: 3D object detection based on roadside cameras is an additional way for autonomous driving to alleviate the challenges of occlusion and short perception range from vehicle cameras. Previous methods for roadside 3D object detection mainly focus on modeling the depth or height of objects, neglecting the stationary of cameras and the characteristic of inter-frame consistency. In this work, we propose a novel framework, namely MOSE, for MOnocular 3D object detection with Scene cuEs. The scene …
3d object 3d object detection abstract arxiv autonomous autonomous driving boosting cameras challenges cs.cv detection driving focus modeling object objects perception type vision
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