AI RESEARCH
SeeU: Seeing the Unseen World via 4D Dynamics-aware Generation
arXiv CS.CV
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ArXi:2512.03350v2 Announce Type: replace Images and videos are discrete 2D projections of the 4D world (3D space + time). Most visual understanding, prediction, and generation operate directly on 2D observations, leading to suboptimal performance. We propose SeeU, a novel approach that learns the continuous 4D dynamics and generate the unseen visual contents. The principle behind SeeU is a new 2D$\to$4D$\to$2D learning framework. SeeU first reconstructs the 4D world from sparse and monocular 2D frames (2D$\to$4D.