Real-world applications have high demands for semantic segmentation methods. Although
semantic segmentation has made remarkable leap-forwards with deep learning, the
performance of real-time methods is not satisfactory. In this work, we propose PP-LiteSeg, a
novel lightweight model for the real-time semantic segmentation task. Specifically, we
present a Flexible and Lightweight Decoder (FLD) to reduce computation overhead of
previous decoder. To strengthen feature representations, we propose a Unified Attention …