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.
Keywords
- Computer Vision: Language and Vision
- Knowledge Representation and Reasoning: Common-Sense Reasoning
- Machine Learning: Interpretability
