Demonstrates improved lane detection accuracy using GAN-based image translation for autonomous driving systems, indicating significant enhancements in nighttime scenarios.
Camera-based lane detection degrades severely at night due to poor illumination and low contrast. We propose a CycleGAN image translation pipeline converting nighttime frames to daytime equivalents, enabling LaneNet to achieve substantially improved accuracy, F1-score, and false positive rate without retraining.
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India et al. (2026) studied this question.
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