An Efficient Network for Lane Segmentation | |
Li, Haoran1,2; Zhao, Dongbin1,2; Chen, Yaran1,2; Zhang, Qichao1,2 | |
2019-04 | |
会议日期 | 2018-10 |
会议地点 | Beijing, China |
英文摘要 | As the basis of scenes understanding for autonomous driving, lane segmentation is always a challenge due to the various illumination conditions, heavy traffics and richly-textured roads. Because of the heavily biased distribution of lane/non-lane pixels, it is hard to achieve satisfying results by using image segmentation networks such as fully convolution neural networks (FCN). In this paper, we propose a new loss function to tackle the unbalanced data distribution problem. It has shown that the loss function significantly improves the performance of available segmentation networks such as FCN on the lane segmentation task. |
语种 | 英语 |
内容类型 | 会议论文 |
源URL | [http://ir.ia.ac.cn/handle/173211/40315] |
专题 | 复杂系统管理与控制国家重点实验室_深度强化学习 |
作者单位 | 1.Institute of Automation, Chinese Academy of Sciences 2.University of Chinese Academy of Sciences |
推荐引用方式 GB/T 7714 | Li, Haoran,Zhao, Dongbin,Chen, Yaran,et al. An Efficient Network for Lane Segmentation[C]. 见:. Beijing, China. 2018-10. |
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