In the Deep Point Clouds course, we're building hardcore fundamentals on 3D Deep Learning. We're learning how to use PointNet, and we're learning how to use Voxelization & 3D CNNs.
But all of it really is the "backbone" to more practical algorithms.
When you look around, you'll notice that engineers don't stick to using backbones and classifiers, they also learn to apply 3D Deep Learning in every day projects, like 3D Object Detection.
In LiDAR, 3D Object Detection is the most common and important application to master; and it was a missing element from my Deep Point Clouds course.
We have learned about classification, and it's now time to learn about object detection.
Just like with Computer Vision, most applications are based on object detection. Whether it's augmented reality, object recognition, drone tracking, autonomous driving, or any other; we must detect objects to understand our surroundings.