Semantic Constraint Based Target Object Recognition

摘要

With the growth of deep learning, object recognition has received increasing interests and its accuracy has been improved significantly in the past few years, However, high-quality recognition largely depends on a large number of learning instances. If the number of learning instances is reduced, it's difficult to maintain realistic recognition accuracy. Moreover, traditional methods usually don't consider the semantic relationship between different regions. Actually, semantic constraint would contribute to improve the recognition accuracy effectively.