现代信息科技2024，Vol.8Issue(3)：164-168,175,6.DOI:10.19850/j.cnki.2096-4706.2024.03.035
融合多尺度通道注意力的开放词汇语义分割模型SAN
An Open Vocabulary Semantic Segmentation Model SAN Integrating Multi Scale Channel Attention
摘要
Abstract
With the development of visual language models,open vocabulary methods have been widely used in identifying categories outside the annotated label.Compared with the weakly supervised and zero sample method,the open vocabulary method is proved to be more versatile and effective.The goal of this study is to improve the lightweight model SAN for open vocabulary segmentation,which introduces a feature fusion mechanism AFF based on multi scale channel attention to improve the model,and improve the dual branch feature fusion method in the original SAN structure.Then,the improved algorithm is evaluated based on multiple semantic segmentation benchmarks,and the results show that the model performance has certain improvement with almost no change in the number of parameters.This improvement plan will help simplify future research on open vocabulary semantic segmentation.关键词
开放词汇/语义分割/SAN/CLIP/多尺度通道注意力Key words
open vocabulary/semantic segmentation/SAN/CLIP/multi scale channel attention分类
信息技术与安全科学引用本文复制引用
武玲,张虹..融合多尺度通道注意力的开放词汇语义分割模型SAN[J].现代信息科技,2024,8(3):164-168,175,6.基金项目
太原师范学院研究生教育教学改革研究课题(SYYJSJG-2154) （SYYJSJG-2154）
