  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.
