4 Dimensional Scene

4D scene understanding aims to represent and reason about dynamic 3D scenes over time, incorporating both spatial and temporal information. Current research focuses on developing models that effectively capture and utilize this 4D data, employing techniques like neural-symbolic reasoning, video diffusion models, and transformer architectures operating on point cloud data or tensorial representations of radiance fields. These advancements improve tasks such as video question answering, scene generation, and panoptic segmentation in dynamic environments, leading to more robust and comprehensive scene understanding in various applications like autonomous driving and virtual reality.