Semantic Enhancement Loss Function Based on Attention Mechanism

Abstract

Panoramic segmentation is an important research direction in computer vision. Considering that different applications have different requirements for semantic segmentation accuracy, a semantic enhancement loss function based on attention mechanism is proposed. By adding attention mechanism, it can enhance the sensitivity to the semantic information of task attention and improve the classification accuracy of specific objects and backgrounds. The experimental results show that the semantic enhancement loss function can effectively improve the classification accuracy of semantic categories required by tasks.