YOLOPoint Joint Keypoint and Object Detection
Fuente:
arXiv
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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866909095412367360 |
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| author | Backhaus, Anton Luettel, Thorsten Wuensche, Hans-Joachim |
| author_facet | Backhaus, Anton Luettel, Thorsten Wuensche, Hans-Joachim |
| contents | 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 and a light-weight network structure, YOLOPoint is able to perform competitively on both the HPatches and KITTI benchmarks. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2402_03989 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | YOLOPoint Joint Keypoint and Object Detection Backhaus, Anton Luettel, Thorsten Wuensche, Hans-Joachim Computer Vision and Pattern Recognition 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 and a light-weight network structure, YOLOPoint is able to perform competitively on both the HPatches and KITTI benchmarks. |
| title | YOLOPoint Joint Keypoint and Object Detection |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2402.03989 |