YOLO is in general 2D algorithm. In your DIJ link they use YOLO2, but latest more accurate version is YOLO3. YOLO has its advantages, mostly it is quite fast and has simple one-stage construction, but as for 2019 YOLO is “outdated”. There are alternatives with better speed/accuracy tradeoff, but mostly YOLO (to my knowlege) is no longer an active project and it’s development framework (darknet) never become popular.
If you want to use 2D object detection the simplest way is to use OpenCV dnn module wrapped in ROS node. That way you can use YOLO, but also more powerful Tensorflow graphs. Unfortunatelly currently OpenCV don’t support NVIDIA CUDA. If you wan’t to use Jetsons it’s better to run Tensorflow/PyTorch models directly in python or C++ wrapped in ROS nodes. NVIDIA also has a ready to use fast models in TensorRT: https://github.com/dusty-nv/ros_deep_learning
Ok, but back to the topic, if anybody knows about labeled point clouds from drones I’m interested