Semantic segmentation using stride spatial pyramid pooling and dual attention decoder.

•We propose an SSPP structure to capture multiscale semantic information.•Attention mechanism is applied to bridge the information gap in segmentation networks.•We propose a new decoder to make full use of the low- and high-level feature maps.•Auxiliary loss is applied to make the network easier to train.•Our method attains state-of-the-art performance on PASCAL VOC 2012, Cityscapes and COCO-Stuff.