3D cameras and innovative algorithms have opened up new avenues for analysing in-cabin behaviour of vehicle occupants. In this talk, we will discuss the different technologies for deriving 3D occupant information in an automotive in-cabin setting, including using 3D cameras such as ToF, structured light, etc. as well as 2D cameras paired with novel algorithms that estimate 3D positions. We will explore the benefits of using 3D occupant information for in-cabin analysis and how it enables more accurate tracking of occupants and their behavior. We will showcase the various use cases that benefit from 3D information, specifically: 1. Optimized airbag deployment 2. User experience and intuitive interaction Furthermore, we will discuss the challenges of implementing 3D occupant information in an automotive in-cabin setting and how to overcome them. We will also touch upon the potential for future research and development in this area, such as combining 3D information with other sensor modalities to achieve even greater accuracy and reliability. Overall, this talk will provide valuable insights into the benefits and challenges of using 3D information for automotive in-cabin analysis and how it can be leveraged to improve safety, comfort, and overall driving experience for occupants.