Vision Centric Autonomous Driving

Vision-centric autonomous driving aims to replace or significantly reduce reliance on LiDAR by using only camera data for perception and decision-making, lowering costs and improving scalability. Current research heavily focuses on developing robust methods for creating bird's-eye-view (BEV) representations from multiple camera images, often employing transformer-based architectures and incorporating temporal information for improved scene understanding and prediction. This approach is advancing the field by enabling more efficient and potentially safer autonomous systems, particularly through improvements in 3D object detection, occupancy prediction, and motion forecasting.