Abstract
Deep learning based data-driven approaches have
been successfully applied in various image understanding applications ranging from object recognition, semantic segmentation to visual question answering. However, the lack of knowledge integration as well as higher-level reasoning capabilities
with the methods still pose a hindrance. In this
work, we present a brief survey of a few representative reasoning mechanisms, knowledge integration methods and their corresponding image understanding applications developed by various groups
of researchers, approaching the problem from a variety of angles. Furthermore, we discuss upon key
efforts on integrating external knowledge with neural networks. Taking cues from these efforts, we
conclude by discussing potential pathways to improve reasoning capabilities