4D radar is a high-resolution long-range radar sensor that not only detects the distance, relative speed, and azimuth of objects, but also their height above the road level. Unlike LiDAR, it works well in all weather conditions, including fog and heavy rain. A state-of-the-art anchor-free 3D object detector CenterPoint is used. It is trained on the 4D radar data of the open dataset Astyx. Because the annotated samples are limited and the 4D radar point clouds are sparse, the 3D bounding box prediction is naturally not so good. It is observed that although vehicles near ego cars could be correctly detected, there are still some false positive predictions and some objects at longer distances that could not be detected. 4D radar object detection and fusion with camera image could boost the performance by a large margin.
The Centerpoint model is used for 4D radar detection and the following figure shows the result of the Centerpoint model.
The following table lists the Centerpoint models supported by the Vitis AI library.
| No | Model Name | Framework |
|---|---|---|
| 1 | centerpoint_0_pt | PyTorch |
| 2 | centerpoint_1_pt | PyTorch |