RTM3D: Real-Time Monocular 3D Detection from Object Keypoints for Autonomous Driving
文献类型：会议论文
| 作者 | Li PX(李培玄)1,2,3,4,5 ; Zhao HC(赵怀慈)1,2,3,5; Liu PF(刘鹏飞)1,2,3,4,5; Cao FD(曹飞道)1,2,3,4,5
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| 出版日期 | 2020 |
| 会议日期 | August 23-28, 2020 |
| 会议地点 | Glasgow, UK |
| 关键词 | Real-time monocular 3D detection Autonomous driving Keypoint detection |
| 页码 | 644-660 |
| 英文摘要 | In this work, we propose an efficient and accurate monocular 3D detection framework in single shot. Most successful 3D detectors take the projection constraint from the 3D bounding box to the 2D box as an important component. Four edges of a 2D box provide only four constraints and the performance deteriorates dramatically with the small error of the 2D detector. Different from these approaches, our method predicts the nine perspective keypoints of a 3D bounding box in image space, and then utilize the geometric relationship of 3D and 2D perspectives to recover the dimension, location, and orientation in 3D space. In this method, the properties of the object can be predicted stably even when the estimation of keypoints is very noisy, which enables us to obtain fast detection speed with a small architecture. Training our method only uses the 3D properties of the object without any extra annotations, category-specific 3D shape priors, or depth maps. Our method is the first real-time system (FPS > 24) for monocular image 3D detection while achieves state-of-the-art performance on the KITTI benchmark. |
| 产权排序 | 1 |
| 会议录 | 2020 European Conference on Computer Vision (ECCV 2020)
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| 会议录出版者 | Springer Science and Business Media Deutschland GmbH |
| 会议录出版地 | Berlin |
| 语种 | 英语 |
| ISBN号 | 978-3-030-58580-8 |
| 源URL | [http://ir.sia.cn/handle/173321/27957]  |
| 专题 | 沈阳自动化研究所_光电信息技术研究室 |
| 通讯作者 | Zhao HC(赵怀慈) |
| 作者单位 | 1.Key Lab of Image Understanding and Computer Vision, Shenyang, China 2.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang, China 3.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China 4.University of Chinese Academy of Sciences, Beijing, China 5.Key Laboratory of Opto-Electronic Information Processing, Chinese Academy of Sciences, Shenyang, China |
| 推荐引用方式 GB/T 7714 | Li PX,Zhao HC,Liu PF,et al. RTM3D: Real-Time Monocular 3D Detection from Object Keypoints for Autonomous Driving[C]. 见:. Glasgow, UK. August 23-28, 2020. |
入库方式： OAI收割
来源：沈阳自动化研究所
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