I am generating images that consist of points, where the object's location is where the most overlap of points occurs.

In this example, the object location is $(25, 51)$.

I am trying to train a model to just finds the location, so I don't care about the classification of the object. Additionally, the shape of the overlapping points where the object is located never changes and will always be that shape.

What is a good model for this objective?

Many of the potential models I've been looking at (CNN, YOLO, and R-CNN) are more concerned with classification than location. Should I search the image for the overlapping dots, create a bound box around them, then retrieve the boxes' coordinates?