Bird's Eye View Perception

Bird's-eye-view (BEV) perception aims to create a top-down, 2D representation of a 3D scene using camera and/or LiDAR data, primarily for autonomous driving applications. Current research focuses on improving the robustness and accuracy of BEV generation, often employing deep learning models like transformers and leveraging techniques such as multi-sensor fusion, and self-supervised learning to address challenges like data scarcity and sensor inconsistencies. This field is crucial for advancing autonomous driving capabilities by providing a unified and interpretable representation of the environment, enabling more reliable perception and decision-making.