# Scene Tokenizer

Driving 3D world models often treat geometry-foundation-model features as future states, yet those features shift with camera viewpoint, so the model must predict scene evolution and camera motion at once. GeoState compresses multi-view features into a view-decoupled scene state that a camera ray queries only at decoding, while camera motion is modeled separately. On Waymo it beats compared world models at every reported horizon and transfers zero-shot to KITTI and nuScenes.

Driving 3D world models often treat geometry-foundation-model features as future states, yet those features shift with camera viewpoint, so the model must predict scene evolution and camera motion at once. GeoState compresses multi-view features into a view-decoupled scene state that a camera ray queries only at decoding, while camera motion is modeled separately. On Waymo it beats compared world models at every reported horizon and transfers zero-shot to KITTI and nuScenes.

SemanTok is a flexible-length video tokenizer that feeds frozen DINOv2 features into its encoder and adds lightweight heads that reconstruct those features from each retained token prefix alone, letting a 201M autoregressive model match or beat a VideoFlexTok model 3.4 times its size and improving semantic alignment at every noise level, including pure noise.

SemanTok is a flexible-length video tokenizer that feeds frozen DINOv2 features into its encoder and adds lightweight heads that reconstruct those features from each retained token prefix alone, letting a 201M autoregressive model match or beat a VideoFlexTok model 3.4 times its size and improving semantic alignment at every noise level, including pure noise.