  Diabetic Retinopathy is the leading cause of blindness in the world. At least
90\% of new cases can be reduced with proper treatment and monitoring of the
eyes. However, scanning the entire population of patients is a difficult
endeavor. Computer-aided diagnosis tools in retinal image analysis can make the
process scalable and efficient. In this work, we focus on the problem of
localizing the centers of the Optic disc and Fovea, a task crucial to the
analysis of retinal scans. Current systems recognize the Optic disc and Fovea
individually, without exploiting their relations during learning. We propose a
novel approach to localizing the centers of the Optic disc and Fovea by
simultaneously processing them and modeling their relative geometry and
appearance. We show that our approach improves localization and recognition by
incorporating object-object relations efficiently, and achieves highly
competitive results.
