Static Scene

Static scene representation and reconstruction are active research areas focusing on accurately capturing and rendering stationary environments from various data sources, including monocular video, event cameras, and multi-view imagery. Current efforts leverage techniques like 3D Gaussian splatting, neural radiance fields (NeRFs), and probabilistic object-level change detection to achieve high-fidelity reconstructions, often incorporating temporal information for improved robustness and efficiency. These advancements are crucial for applications ranging from immersive virtual reality experiences to autonomous robot navigation and map updating in dynamic environments, improving the accuracy and reliability of scene understanding in various fields.