Dynamic Scene

Dynamic scene representation aims to accurately model and render three-dimensional scenes undergoing changes over time, focusing on efficient and realistic novel view synthesis. Current research heavily utilizes neural implicit representations, such as Neural Radiance Fields (NeRFs) and Gaussian splatting, often incorporating techniques like spatio-temporal modeling, motion factorization, and semantic segmentation to improve accuracy and efficiency, particularly for complex scenes with multiple moving objects. This field is crucial for advancements in autonomous driving, robotics, virtual and augmented reality, and video editing, enabling applications ranging from realistic simulations to interactive 3D content creation.