AI RESEARCH
Inferring Compositional 4D Scenes without Ever Seeing One
arXiv CS.CV
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ArXi:2512.05272v2 Announce Type: replace Scenes in the real world are often composed of several static and dynamic objects. Capturing their 4-dimensional structures, composition and spatio-temporal configuration in-the-wild, though extremely interesting, is equally hard. Therefore, existing works often focus on one object at a time, while relying on some category-specific parametric shape model for dynamic objects. This can lead to inconsistent scene configurations, in addition to being limited to the modeled object categories.