2D and 3D Vision for Autonomous Driving (AD)

The process of perception in self-driving cars uses a combination of high-tech sensors and cameras, combined with state-of-the-art software to process and comprehend the environment around the vehicle, in real-time. Perception in self-driving cars is crucial to the safe and reliable operation because the data received from these processes fuel the core decision-making that figures out how the vehicle should move next; such that, the car is headed in the right direction (to its destination) and is not risking the lives of humans in, and around the car, while doing so. This talk presents both 2D and 3D machine perception tasks in the context of autonomous driving (AD). This includes lane line detection, traffic sign identification, steering angle prediction, and pothole detection on RGB images along with the perception tasks such as 3D object detection and segmentation on Lidar point clouds using LiDAR point clouds and Lidar Images. 

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