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Found 4 papers, 3 papers with code
Keep your Eyes on the Lane: Real-time Attention-guided Lane Detection
Modern lane detection methods have achieved remarkable performances in complex real-world scenarios, but many have issues maintaining real-time efficiency, which is important for autonomous vehicles.
Ranked #6 on
Lane Detection
on LLAMAS
PolyLaneNet: Lane Estimation via Deep Polynomial Regression
One of the main factors that contributed to the large advances in autonomous driving is the advent of deep learning.
Ranked #9 on
Lane Detection
on LLAMAS
Deep traffic light detection by overlaying synthetic context on arbitrary natural images
By providing real image samples with traffic context to the network, the model learns to detect and classify elements of interest, such as pedestrians, traffic signs, and traffic lights.
Deep Traffic Sign Detection and Recognition Without Target Domain Real Images
The method does not aim at overcoming the training with real data, but to be a compatible alternative when the real data is not available.
