Given two spatial data sets A and B, a top-k spatial join retrieves the k objects from A or B that intersect the largest number of objects from the other data set. Depending on the application requirements, there exist several variations of the problem. For instance, B may be a point data set, and the goal may be to retrieve the regions of A that contain the maximum number of points. The processing of such queries with conventional spatial join algorithms is expensive. However, several improvements are possible based on the fact that we only require a small subset of the result (instead of all intersection/containments pairs). In this paper, we propose output-sensitive algorithms for top-k spatial joins that utilize a variety of optimizations for reducing the overhead.