Directly comparing image pixels to decide iftheybelong tothe same cluster leads to poor results because they are strongly impacted by factors irrelevant to clustering, such as exact viewpoint or lighting.

Further, the model is regularized to align the importance scores with human knowledge, so that the unintended model behaviors are eliminated.