计算机科学与探索2024，Vol.18Issue(3)：707-717,11.DOI:10.3778/j.issn.1673-9418.2209110
MFFNet:多级特征融合图像语义分割网络
MFFNet:Image Semantic Segmentation Network of Multi-level Feature Fusion
摘要
Abstract
In the task of image semantic segmentation,most methods do not make full use of features of different scales and levels,but directly upsampling,which will cause some effective information to be dismissed as redundant information,thus reducing the accuracy and sensitivity of segmentation of some small categories and similar categories.Therefore,a multi-level feature fusion network(MFFNet)is proposed.MFFNet uses encoder-decoder structure,during the encoding stage,the context information and spatial detail information are obtained through the context information extraction path and spatial information extraction path respectively to enhance the inter-pixel correlation and boundary accuracy.During the decoding stage,a multi-level feature fusion path is designed,and the context information is fused by the mixed bilateral fusion module.Deep information and spatial information are fused by high-low feature fusion module.The global channel-attention fusion module is used to obtain the connections between different channels and realize global fusion of different scale information.The MIoU(mean intersection over union)of MFFNet network on the PASCAL VOC 2012 and Cityscapes validation sets is 80.70%and 76.33%,respectively,achieving better segmentation results.关键词
编码器-解码器/上下文信息/空间信息/特征融合Key words
encoder-decoder/context information/spatial information/feature fusion分类
信息技术与安全科学引用本文复制引用
王燕,南佩奇..MFFNet:多级特征融合图像语义分割网络[J].计算机科学与探索,2024,18(3):707-717,11.基金项目
国家自然科学基金(61863025).This work was supported by the National Natural Science Foundation of China(61863025). （61863025）
