Make data set from the ground truth.

• Decode the KITTI ground truth result.
• Cut the segment of cloud that contains each object -> to make an object classification dataset.

• Pretreatment of the raw data, and build a PointNet++ to classify them. (Classfication precision reaches 90%) Mine model could be found here in Baidu Yun with extraction code '5u6q' .

• Implement the model to the whole KITTI set for detection task. (Traditional segmentation + Pointnet++ classification)

• Analysis the results, show the recall and precision.
• What todo in the future.