Machine Learning is essential for the success of safety-critical, holistic perception. At the same time, learned approaches need investment to achieve flexibility. In the ever-evolving landscape of 3D sensor perception, this statement encapsulates the critical balance between traditional rule-based algorithms and deep learning approaches. While the automotive industry has been the cradle of safety-critical 3D sensor perception, the static sensor sector has leaned on traditional methods.