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RoGSW4RLD is introduced, a feed-forward framework that lifts synchronized multi-camera rollouts into a unified, time-queryable metric 4D Gaussian field and directly reconstructs the visual future generated by existing world models.
A feed-forward, spatially constrained framework that grounds task-relevant objects and generates position-aware subtasks without an iterative task–scene refinement loop is proposed and confidence-guided verification improves the unweighted scene-average Relaxed Accuracy F1.
This work proposes a novel framework that overcomes this limitation by tightly coupling a DFM with a cascade MVS pipeline through a bidirectional mutual refinement strategy, and introduces a prior-guided cost volume refinement mechanism that effectively integrates multi-view and monocular information via attention-base...
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