AI RESEARCH
GEM: Gaussian Evolution Model for Occupancy Forecasting and Motion Planning
arXiv CS.CV
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ArXi:2605.17682v1 Announce Type: new Future 3D semantic occupancy forecasting and motion planning are central to autonomous driving, as they require models to reason about how surrounding scenes evolve and how the ego vehicle should act. Existing occupancy world models commonly discretize scenes into latent embeddings, volumetric features, or quantized tokens, and forecast future states through fixed-step autoregressive generation.