SOURCE-LINKED INTELLIGENCE
Underwater C3-JEPA: An Object-Centric Cross-View World Model for ROV Salvage
We present Underwater C$^{3}$-JEPA (cross-view, control-conditioned, context-extended), an object-centric multi-view predictive world model for near-field heavy-load underwater ROV salvage. Without contact sensors, it predicts in latent space how the task-object state evolves through contact interaction and under the hydrodynamic lag of the vehicle, from synchronized multi-view RGB observations and vehicle control signals. C$^{3}$-JEPA encodes multi-camera observations into task-object and context tokens, fuses cross-camera evidence through held-out-view attention, and directly predicts future
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-24T17:45:42.000Z
First collected: 2026-09-25T06:12:46.948Z. This is not the publication date.