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An Efficient Semantic Segmentation Method using Pyramid ShuffleNet V2 with Vortex Pooling

Research output: Chapter in Book/Report/Conference proceedingConference contribution

  • Jiansheng Dong
  • Jingling Yuan
  • Lin Li
  • Xian Zhong
  • Weiru Liu
Original languageEnglish
Title of host publication31st International Conference on Tools with Artificial Intelligence (ICTAI2019)
Publisher or commissioning bodyInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages8
DateAccepted/In press - 27 Aug 2019
Event International Conference on Tools with Artificial Intelligence - Portland, United States
Duration: 4 Nov 20196 Nov 2019
Conference number: 31
http://www.ictai2019.org/

Conference

Conference International Conference on Tools with Artificial Intelligence
Abbreviated titleICTAI2019
CountryUnited States
CityPortland
Period4/11/196/11/19
Internet address

Abstract

—Efficient and accurate semantic segmentation is particularly important especially for applications like autonomous driving which requires real-time inference speed and high performance. Many works try to compromise spatial resolution to achieve real-time inference speed, which leads to poor performance. As a result, real-time segmentation task for embedded devices is still an open problem. In this paper, we focus on building a network with better performance possible
while still achieve real-time inference speed. We first use a pyramid kernel size to capture more spatial information instead of using just a 3×3 kernel size for DWConvolution in ShuffleNet v2. Meanwhile, an efficient Vortex Pooling module is employed to aggregate the contextual information and generate highresolution features. Compared with other state-of-the-art realtime semantic segmentation networks, the proposed network achieves similar inference speed and better performance on embedded device. Specifically, we achieve state-of-the-art 73.46% mean IoU on Cityscapes test dataset, for a 768×1024 input, a speed of 46.1 frames per second on NVIDIA Jetson AGX Xavier embedded development board is achieved.

    Research areas

  • semantic segmentation, real-time, embedded

Event

International Conference on Tools with Artificial Intelligence

Abbreviated titleICTAI2019
Conference number31
Duration4 Nov 20196 Nov 2019
CityPortland
CountryUnited States
Web address (URL)
Degree of recognitionInternational event

Event: Conference

Documents

Documents

  • Full-text PDF (accepted author manuscript)

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