轻量模型的眼睛语义分割

在本文中，我们提出了一种多类眼睛分割方法，该方法可以运行实时推理的硬件限制。我们的方法包括三个主要阶段：从输入中获取灰度图像，使用深层网络分割三个不同的眼睛区域，并使用启发式滤镜去除不正确的区域。..

Eye Semantic Segmentation with a Lightweight Model

In this paper, we present a multi-class eye segmentation method that can run the hardware limitations for real-time inference. Our approach includes three major stages: get a grayscale image from the input, segment three distinct eye region with a deep network, and remove incorrect areas with heuristic filters.Our model based on the encoder decoder structure with the key is the depthwise convolution operation to reduce the computation cost. We experiment on OpenEDS, a large scale dataset of eye images captured by a head-mounted display with two synchronized eye facing cameras. We achieved the mean intersection over union (mIoU) of 94.85% with a model of size 0.4 megabytes. The source code are available https://github.com/th2l/Eye_VR_Segmentation