Recently, Jige Technology proposed a new framework called DriveDreamer4D, aimed at leveraging prior knowledge from world models to improve the reconstruction quality of 4D driving scenes. Traditional 4D scene reconstruction methods primarily rely on two main approaches: NeRF and 3DGS. NeRF is like a super painter, capable of rendering a collection of photos into a 3D model using neural networks. On the other hand, 3DGS simulates various objects in the scene using a set of three-dimensional Gaussian functions. However, both methods have their limitations.

'OmniRe' technology has been jointly developed by several top universities and research institutions, aiming to comprehensively reconstruct urban scenes, including vehicles, pedestrians, and bicycles. Unlike traditional methods that rely on local perspectives, 'OmniRe' integrates multi-angled information to achieve a more accurate capture of urban environments, significantly enhancing reconstruction quality. This groundbreaking advancement holds vital importance for fields such as urban planning, autonomous driving, and augmented reality. 'OmniRe' not only generates high-precision 3D models but also possesses the capability to efficiently process large amounts of data, expediting...