Modern generators often violate basic physics—e.g., inconsistent shadows, geometry, and measurement models limiting trust for video synthesis and computational imaging. We propose finite-time Schrödinger-Bridge (SB) world models that cast generation as entropy-regularized optimal transport from a simple prior to a physics- and data-consistent distribution. Unlike post-hoc corrections, our approach injects structure along the transport path: multi-view geometry (reprojection/epipolar constraints, homographies, depth-aware warps) for video, and differentiable optical operators (PSF-based defocus, lightweight Fourier propagation for coherent/partially coherent settings) for imaging. With known poses, we penalize reprojection and warp-aligned photometric/feature errors; with unknown poses, a compact head estimates motion/flow with cycle-consistency. Compact UNet/ViT backbones and short SB horizons target efficiency. Evaluation spans 3D consistency metrics, physics fidelity via forward-simulation error, and generative quality/efficiency (FID/KID, FVD) against strong diffusion baselines, plug-and-play data-consistency, and unconstrained SB. By constraining the path rather than only the endpoint, the method aims to shorten sampling while improving cross-view coherence and physical plausibility across sensors (cameras, microscopes, medical scanners).