Precise and accurate segmentation over boundary areas is important in semantic segmentation. The commonly used convolutional operators tend to smooth and blur local detail cues, making it difficult for deep learning models to generate accurate boundary predictions. In this paper, we propose an efficient boundary-aware convolution operator to boost the boundary modeling capacity for semantic segmentation, named Semantic Difference Convolution (SDC). The SDC is sensitive to the inter-class boundar…