Deep multi-scale and multi-modal fusion for 3D object detection
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We propose a deep multimodal fusion method to make full use of the advantages of RGB image data and point clouds.
Highlights. •. We propose a multi-scale feature fusion method from different resolution feature maps for 3D object detection.
In order to make better use of the advantages of image data and point cloud data, a 3D object detection method based on Deep Multi-scale and Multi-modal Fusion ...
TL;DR: The authors improve 3D detection accuracy by exploring point cloud inner order, which contains context information but neglected before, and propose a ...
Dec 10, 2022 · We propose a general multi-modal fusion framework Multi-Sem Fusion (MSF) to fuse the semantic information from both the 2D image and 3D points scene parsing ...
Sep 5, 2024 · Multi-sensor fusion is crucial for accurate 3D object detection in autonomous driving, with cameras and LiDAR being the most commonly used ...
Multi-modal fusion plays a critical role in 3D object detection, overcoming the inherent limitations of single-sensor perception in autonomous driving.
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Oct 8, 2024 · Our proposed DPFusion demonstrates competitive results in 3D object detection, achieving a mean Average Precision (mAP) of 70.4 and a nuScenes detection score ...
In this paper, we propose a novel Object-centric. Fusion (ObjectFusion) paradigm, which completely gets rid of camera-to-BEV transformation during fusion to ...