ICNet for Real-Time Semantic Segmentation on High-Resolution Images

We focus on the challenging task of real-time semantic segmentation in thispaper. It finds many practical applications and yet is with fundamentaldifficulty of reducing a large portion of computation for pixel-wise labelinference. We propose an image cascade network (ICNet) that incorporatesmulti-resolution branches under proper label guidance to address thischallenge. We provide in-depth analysis of our framework and introduce thecascade feature fusion unit to quickly achieve high-quality segmentation. Oursystem yields real-time inference on a single GPU card with decent qualityresults evaluated on challenging datasets like Cityscapes, CamVid andCOCO-Stuff.