Semantic and Geometric-Aware Day-to-Night Image Translation Network.

Autonomous driving systems heavily depend on perception tasks for optimal performance. However, the prevailing datasets are primarily focused on scenarios with clear visibility (i.e.

GAN-Based LiDAR Translation between Sunny and Adverse Weather for Autonomous Driving and Driving Simulation.

Autonomous driving requires robust and highly accurate perception technologies. Various deep learning algorithms based on only image processing satisfy this requirement, but few such algorithms are based on LiDAR. However, images are only one part of the perceptible sensors in an autonomous driving vehicle; LiDAR is also essential for the recognition of driving environments.