Desnity Peak clustering is an interesting idea, but is still centroid based and will have many of the same issues as K-Means (but may pick better centroids for this case). It also involves a little bit of parameter tuning (particularly with regard to bandwidth), and can be relatively slow if not suitably accelerated with space indexing structures such as kd-trees or cover-trees.

Is it included in sklearn?