Abstract
The IEEE Low-Power Image Recognition Challenge (LPIRC) is an annual competition started in 2015 that encourages joint hardware and software solutions for computer vision systems with low latency and power. Track 1 of the competition in 2018 focused on the innovation of software solutions with fixed inference engine and hardware. This decision allows participants to submit models online and not worry about building and bringing custom hardware on-site, which attracted a historically large number of submissions. Among the diverse solutions, the winning solution proposed a quantization-friendly framework for MobileNets that achieves an accuracy of 72.67% on the holdout dataset with an average latency of 27ms on a single CPU core of Google Pixel2 phone, which is superior to the best real-time MobileNet models at the time.
Abstract (translated)
IEEE低功耗图像识别挑战（LPIRC）是一项于2015年开始的年度竞赛，旨在鼓励针对低延迟和低功耗计算机视觉系统的联合硬件和软件解决方案。2018年的第一项比赛重点是软件解决方案的创新，包括固定推理引擎和硬件。这个决定允许参与者在线提交模型，而不必担心在现场构建和带来定制硬件，这吸引了历史上大量的提交。在众多的解决方案中，胜出的解决方案提出了一个便于量化的mobilenet框架，在google pixel2手机的单CPU核心上，对holdout数据集的精度达到72.67%，平均延迟为27ms，优于当时最好的实时mobilenet模型。
URL
https://arxiv.org/abs/1903.06791
