Learning Action-Conditional and Object-Centric Gaussian Splatting World Models for Rigid Objects 事件

Learning Action-Conditional and Object-Centric Gaussian Splatting World Models for Rigid Objects arXiv:2606.01950v1 Announce Type: cross Abstract: World models enable intelligent agents to predict the consequences of their actions on the environment. In this paper, we propose Multi Rigid Object Gaussian World Model (MRO-GWM), a novel model that learns action-conditional dynamics of rigid objects in 3D. By representing the scene by object-centric Gaussians, we can represent arbitrary object shap