Urban Scene

Urban scene analysis focuses on computationally representing and understanding the complex visual and geometric properties of city environments, aiming to improve applications like autonomous driving and urban planning. Current research heavily utilizes neural rendering techniques, such as 3D Gaussian splatting and Neural Radiance Fields (NeRFs), often incorporating LiDAR data and addressing challenges like reflection noise removal, moving object detection, and view extrapolation. These advancements enable more accurate 3D reconstruction, improved object detection, and the generation of realistic synthetic data for training perception models, ultimately contributing to safer and more efficient urban systems.