AFDet: Anchor Free One Stage 3D Object Detection
Runzhou Ge, Zhuangzhuang Ding, Yihan Hu, Yu Wang, Sijia Chen, Li Huang, Yuan Li
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ReproduceCode
- github.com/CarkusL/CenterPointpytorch★ 225
- github.com/stevewongv/sparse2densepytorch★ 80
- github.com/chowkamlee81/CentrePointNetpytorch★ 11
- github.com/mon95/centerpoint-mapspytorch★ 7
- github.com/15526837635/CenterPointpytorch★ 4
- github.com/abhigoku10/CenterPoint_PCpytorch★ 2
- github.com/safetylab24/FusionCVCPpytorch★ 1
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.