Feb. 7, 2024, 5:47 a.m. | Anton Backhaus Thorsten Luettel Hans-Joachim Wuensche

cs.CV updates on arXiv.org arxiv.org

Intelligent vehicles of the future must be capable of understanding and navigating safely through their surroundings. Camera-based vehicle systems can use keypoints as well as objects as low- and high-level landmarks for GNSS-independent SLAM and visual odometry. To this end we propose YOLOPoint, a convolutional neural network model that simultaneously detects keypoints and objects in an image by combining YOLOv5 and SuperPoint to create a single forward-pass network that is both real-time capable and accurate. By using a shared backbone …

convolutional neural network cs.cv detection future independent intelligent low network neural network objects slam systems through understanding vehicles visual

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