Adversarial network integrating dual attention and sparse representation for semi-supervised semantic segmentation

Ge Jin, Chuancai Liu, Xu Chen

Abstract: Highlights•A semi-supervised GAN framework for semantic segmentation is proposed.•The dual attention is proposed to model the global and local semantic dependencies.•The sparse representation module is adopted to further improve the performance.•The focal attention map is proposed to enhance the robustness of the model.•Extensive experiments are conducted to verify the effectiveness of our method.