  The remarkable recent advances in object-centric generative world models
raise a few questions. First, while many of the recent achievements are
indispensable for making a general and versatile world model, it is quite
unclear how these ingredients can be integrated into a unified framework.
Second, despite using generative objectives, abilities for object detection and
tracking are mainly investigated, leaving the crucial ability of temporal
imagination largely under question. Third, a few key abilities for more
faithful temporal imagination such as multimodal uncertainty and
situation-awareness are missing. In this paper, we introduce Generative
Structured World Models (G-SWM). The G-SWM achieves the versatile world
modeling not only by unifying the key properties of previous models in a
principled framework but also by achieving two crucial new abilities,
multimodal uncertainty and situation-awareness. Our thorough investigation on
the temporal generation ability in comparison to the previous models
demonstrates that G-SWM achieves the versatility with the best or comparable
performance for all experiment settings including a few complex settings that
have not been tested before.
