论文标题
嵌入位置的车道检测
Lane detection with Position Embedding
论文作者
论文摘要
最近，Lane检测在自主驾驶方面取得了长足的进步。 RESA（经常性功能切换聚合器）基于图像分割。它提出了一个新型的模块，可在普通CNN进行初步特征提取后富集车道功能。对于Tusimple数据集，场景不太复杂，巷具有更突出的空间特征。根据RESA，我们介绍了嵌入的位置方法以增强空间特征。实验结果表明，该方法在Tusimple数据集上达到了最佳准确性96.93％。
Recently, lane detection has made great progress in autonomous driving. RESA (REcurrent Feature-Shift Aggregator) is based on image segmentation. It presents a novel module to enrich lane feature after preliminary feature extraction with an ordinary CNN. For Tusimple dataset, there is not too complicated scene and lane has more prominent spatial features. On the basis of RESA, we introduce the method of position embedding to enhance the spatial features. The experimental results show that this method has achieved the best accuracy 96.93% on Tusimple dataset.
