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

Hengshuang Zhao; Xiaojuan Qi; Xiaoyong Shen; Jianping Shi; Jiaya Jia

ECCV 2018poster2006 citations

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

Hengshuang Zhao, Xiaojuan Qi, Xiaoyong Shen, Jianping Shi, Jiaya Jia

Abstract

We focus on the challenging task of real-time semantic segmentation in this paper. It finds many practical applications and yet is with fundamental difficulty of reducing a large portion of computation for pixel-wise label inference. We propose an image cascade network (ICNet) that incorporates multi-resolution branches under proper label guidance to address this challenge. We provide in-depth analysis of our framework and introduce the cascade feature fusion unit to quickly achieve high-quality segmentation. Our system yields real-time inference on a single GPU card with decent quality results evaluated on challenging datasets like Cityscapes, CamVid and COCO-Stuff.

BibTeX

@inproceedings{eccv2018_icnetforrealtime,
  title = {ICNet for Real-Time Semantic Segmentation on High-Resolution Images},
  author = {Hengshuang Zhao and Xiaojuan Qi and Xiaoyong Shen and Jianping Shi and Jiaya Jia},
  booktitle = {ECCV 2018},
  year = {2018}
}