Align Images Before You Generate

respondences from the diffusion model's intermediate features, and an aligned area aggregator that integrates messages from only matching regions to avoid ambiguous information interactions. Given the native correspondences as guidance, CorrAdapter can enhance spatiotemporal consistency without any auxiliary inputs, and remains trainingfree and baseline-agnostic, which enables it to generalize seamlessly to various generation tasks. Additionally, we provide an optional training scheme to explore furtherimproved possibilities. Experiments on both static multiview generation and dynamic video generation show that CorrAdapter consistently improves spatiotemporal consistency and perceptual quality over strong baselines, offering a simple yet versatile drop-in approach to geometrically faithful multi-image diffusion.