LiDAR Sensor modeling and Data augmentation with GANs for Autonomous driving

Understand

In the autonomous driving domain, data collection and annotation from real vehicles are expensive and sometimes unsafe.

• Simulators are often used for data augmentation, which requires realistic sensor models that are hard to formulate and model in closed forms.
• Instead, sensors models can be learned from real data.
• The main challenge is the absence of paired data set, which makes traditional supervised learning techniques not suitable.