Open AccessExcavating effective information in different stage of backbone to improve semantic segmentation results
Author(s) -
Huihui Han,
Lei Fan
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1325/1/012081
Subject(s) - pascal (unit) , segmentation , computer science , benchmark (surveying) , artificial intelligence , test set , set (abstract data type) , task (project management) , image segmentation , pattern recognition (psychology) , machine learning , engineering , geography , systems engineering , programming language , geodesy
To overcome the two difficulties in semantic segmentation task:1) the presence of multi-scale objects, 2) the loss of spatial resolution, a new semantic segmentation model is designed in this paper, which can explore effective information from different stage of backbone. Extensive experiments conducted on two public benchmark datasets have proved the effectiveness of each module, and the new model achieves 73.62% mIoU on Cityscapes test set and 79.88% mIoU on PASCAL VOC 2012 test set.