SCOPE-Occ: Scene-Conditioned Probe Lifecycles for Trajectory-Free Camera-Only Occupancy World Modeling

Camera-only occupancy world models forecast future 3D semantic scenes from historical observations. Existing approaches often condition on future ego trajectories, which require an upstream planner or predictor and may introduce oracle dependence or compounding errors. Without such inputs, models must infer how scenes evolve and when and where representational capacity is needed. We present SCOPE-Occ, a trajectory-free camera-only occupancy world model that treats sparse queries as scene-conditioned sensing probes. Its Scene-Conditioned Probe Lifecycle Field (SPLF) predicts temporal support functions governing each probe's emergence, persistence, and termination, supervised by probe-level support matching and scene-level capacity calibration. These signals route spatial evolution in Lifecycle-Routed Probe Dynamics (LPD), where persistent and emerging probes follow distinct update paths integrating observed ego-motion context, local visual evidence, learned mobility, and lifecycle-gated relational interactions. Existence scores further gate probe contributions to future occupancy decoding. On Occ3D-nuScenes, SCOPE-Occ outperforms prior trajectory-free camera-only methods, achieving 21.68 mIoU and 45.26 IoU averaged over the 1-3s forecasting horizons, without future ego trajectories at inference.