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Found 4 papers, 1 papers with code
Multi-Class Lane Semantic Segmentation using Efficient Convolutional Networks
Several studies leverage a semantic segmentation network to extract robust lane features, but few of them can distinguish different types of lanes.
DSNet: An Efficient CNN for Road Scene Segmentation
Although the deep learning-based road scene segmentation can achieve very high accuracy, its complexity is also very high for developing real-time applications.
Efficient Dense Modules of Asymmetric Convolution for Real-Time Semantic Segmentation
Real-time semantic segmentation plays an important role in practical applications such as self-driving and robots.
Ranked #10 on
Semantic Segmentation
on CamVid
Efficient Road Lane Marking Detection with Deep Learning
Lane mark detection is an important element in the road scene analysis for Advanced Driver Assistant System (ADAS).
Ranked #14 on
Semantic Segmentation
on CamVid
