Perhaps somebody here can help me with a sideproject that I'm working on. I'm trying to figure out the topology of a neural network that is capable of detecting the location and orientation of a given object. Say, a wrench. I don't want to use heatmaps (e.g. [1]) because they give just the location of the object and not the orientation. So the problem is basically how to choose the output quantities and how to encode…
There are algorithms for stuff just like that in OpenCV. Maybe you could find some inspiration or clarification by reading through the source code for the algorithms for a brief description?
But I was hoping for a more scientific answer. Like how do researchers approach this problem typically? And is there a strong consensus in this area among researchers?
It seems like such a general problem.