AFDet: Anchor Free One Stage 3D Object Detection

• URL: http://arxiv.org/abs/2006.12671v2
• Date: Tue, 30 Jun 2020 07:03:40 GMT
• Title: AFDet: Anchor Free One Stage 3D Object Detection
• Authors: Runzhou Ge, Zhuangzhuang Ding, Yihan Hu, Yu Wang, Sijia Chen, Li Huang, Yuan Li
• Abstract summary: High-efficiency point cloud 3D object detection is important for many robotics applications including autonomous driving. Most previous works try to solve it using anchor-based detection methods which come with two drawbacks: post-processing is relatively complex and computationally expensive; tuning anchor parameters is tricky. We are the first to address these drawbacks with an anchor free and Non-Maximum Suppression free one stage detector called AFDet.
• Score: 9.981769027320551
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: High-efficiency point cloud 3D object detection operated on embedded systems is important for many robotics applications including autonomous driving. Most previous works try to solve it using anchor-based detection methods which come with two drawbacks: post-processing is relatively complex and computationally expensive; tuning anchor parameters is tricky. We are the first to address these drawbacks with an anchor free and Non-Maximum Suppression free one stage detector called AFDet. The entire AFDet can be processed efficiently on a CNN accelerator or a GPU with the simplified post-processing. Without bells and whistles, our proposed AFDet performs competitively with other one stage anchor-based methods on KITTI validation set and Waymo Open Dataset validation set.

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