4 Dimensional Representation

Four-dimensional (4D) representation focuses on modeling dynamic 3D scenes, capturing both spatial geometry and temporal evolution. Current research emphasizes developing efficient and physically accurate methods for 4D content generation and understanding, often employing neural networks like diffusion models and Gaussian splatting, along with neural-symbolic approaches to incorporate physics priors. These advancements are improving applications in areas such as virtual and augmented reality (XR/VR), video question answering, and dynamic 3D asset creation for gaming and design, by enabling more realistic and controllable simulations of the physical world. The ability to accurately represent and manipulate 4D data is driving progress in various fields requiring the understanding and generation of dynamic visual content.