Large Scale Urban Scene

Large-scale urban scene modeling aims to create realistic, high-fidelity digital representations of entire cities or large urban areas, focusing on accurate reconstruction of both static and dynamic elements like buildings, vehicles, and pedestrians. Current research emphasizes efficient algorithms and model architectures, such as neural radiance fields (NeRFs) and Gaussian splatting, often incorporating scene graphs and other techniques to handle the complexity and scale of these environments. This work is crucial for applications in urban planning, autonomous navigation, virtual and augmented reality, and computer vision research, providing valuable tools for analysis, simulation, and visualization of complex urban environments.