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The 2020 Low-Power Computer Vision Challenge

机译:2020低电脑视觉挑战

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摘要

AI computer vision has advanced significantly in recent years. IoT and edge computing devices such as mobile phones have become the primary computing platform for many end users. Mobile devices such as robots and drones that rely on batteries demand for energy efficient computation. Since 2015, the IEEE Annual International Low-Power Computer Vision Challenge (LPCVC) was held to identify energy-efficient AI and computer vision solutions. The 2020 LPCVC includes three challenge tracks: (1) PyTorch UAV Video Track, (2) FPGA Image Track, and (3) On-device Visual Intelligence Competition (OVIC) Tenforflow Track. This paper summarizes the 2020 winning solutions from the three tracks of LPCVC competitions. Methods and future directions for energy-efficient AI and computer vision research are discussed.
机译:近年来,AI计算机愿景显着提出。 IOT和Edge Computing设备(如移动电话)已成为许多最终用户的主要计算平台。 依赖电池的机器人和无用者等移动设备对节能计算的需求。 自2015年以来,举行了IEEE年度国际低电脑视觉挑战(LPCVC)以确定节能AI和计算机视觉解决方案。 2020 LPCVC包括三个挑战轨道:(1)Pytorch UAV视频轨道,(2)FPGA图像轨道,和(3)设备上的视觉智能竞争(Ovic)Tenforflow轨道。 本文总结了来自LPCVC比赛三轨的2020个获胜解决方案。 讨论了节能AI和计算机视觉研究的方法和未来方向。

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