The Low-Power Image Recognition Challenge (LPIRC, https://rebootingcomputing.ieee.org/lpirc) is an annual competition started in 2015. The competition identifies the best technologies that can classify and detect objects in images efficiently (short execution time and low energy consumption) and accurately (high precision). Over the four years, the winners' scores have improved more than 24 times. As computer vision is widely used in many battery-powered systems (such as drones and mobile phones), the need for low-power computer vision will become increasingly important. This paper summarizes LPIRC 2018 by describing the three different tracks and the winners' solutions.
@article{arxiv.1810.01732,
title = {2018 Low-Power Image Recognition Challenge},
author = {Sergei Alyamkin and Matthew Ardi and Achille Brighton and Alexander C. Berg and Yiran Chen and Hsin-Pai Cheng and Bo Chen and Zichen Fan and Chen Feng and Bo Fu and Kent Gauen and Jongkook Go and Alexander Goncharenko and Xuyang Guo and Hong Hanh Nguyen and Andrew Howard and Yuanjun Huang and Donghyun Kang and Jaeyoun Kim and Alexander Kondratyev and Seungjae Lee and Suwoong Lee and Junhyeok Lee and Zhiyu Liang and Xin Liu and Juzheng Liu and Zichao Li and Yang Lu and Yung-Hsiang Lu and Deeptanshu Malik and Eunbyung Park and Denis Repin and Tao Sheng and Liang Shen and Fei Sun and David Svitov and George K. Thiruvathukal and Baiwu Zhang and Jingchi Zhang and Xiaopeng Zhang and Shaojie Zhuo},
journal= {arXiv preprint arXiv:1810.01732},
year = {2018}
}
Comments
13 pages, workshop in 2018 CVPR, competition, low-power, image recognition