author: biofizzatreya
score: 9 / 10

TODO: Summarize the paper: The paper proposes a method to convert convolutional network based object detection in stereo to LIDAR type point cloud representations. They do this because objects far away are smaller and traditional conv-nets fail to detect them properly.

Then, this depth map is used to calculate the x,y and z coordinates and converted into a point cloud representation. image

The point-cloud is called a pseudo-LIDAR signal. The pseudo-LIDAR representation along with the monocular images are fed into 3d-object detection pipelines.

The paper does not develop any neural network architecture, instead it applies existing 3d object detection architectures on the pseudo-LIDAR point-cloud data. They evaluate their approach on the KITTI dataset. The pseudo-LIDAR is also back projected to LIDAR data to compare the accuracy. image image image