search

sshaoshuai / PointRCNN

PointRCNN: 3D Object Proposal Generation and Detection from Point Cloud, CVPR 2019.
MIT License
1.7k stars 425 forks source link

Use the point cloud frame generated by Carla for prediction and training #218

Open S-kewen opened 1 year ago

S-kewen commented 1 year ago

Hi Shaoshuai:

First of all thank you very much for your contribution, this code is very powerful.

I am recently trying to use PointRCNN to predict the lidar point cloud frame generated by Carla, but the results are not good. I guess the frame generated by Carla is different from KITTI (I used KITTI to reproduce the results successfully)

So I tried to collect the dataset (KITTI-format) in Carla for PointRCNN training (rpn+rcnn), but I trained according to the default parameters and found that the result is still not ideal, I would like to ask the point cloud frame Does intensity matter? Because the intensity in Carla only refers to the distance, it is not real.

Here is the result of the Carla dataset: Car AP@0.70, 0.70, 0.70: bbox AP:34.6747, 31.2628, 31.0747 bev AP:16.8469, 15.9205, 17.7584 3d AP:13.8553, 12.0301, 14.5156 aos AP:25.04, 23.67, 23.37 Car AP@0.70, 0.50, 0.50: bbox AP:34.6747, 31.2628, 31.0747 bev AP:51.1212, 42.6968, 43.5934 3d AP:48.2478, 35.7272, 36.8692 aos AP:25.04, 23.67, 23.37

Looking forward to your reply, thanks!