MegaFlow: Zero-Shot Large Displacement Optical Flow

Accurate estimation of large displacement optical flow re-mains a critical challenge. Existing methods typically rely on iterativelocal search or/and domain-specific fine-tuning, which severely limits theirperformance in large displacement and zero-shot generalization scenarios.To overcome this, we introduce MegaFlow, a simple yet powerful model forzero-shot large displacement optical flow. Rather than relying on highlycomplex, task-specific architectural designs, MegaFlow adapts powerfulpre-trained vision priors to produce temporally consistent motion fields.In particular, we formulate flow estimation as a global matching problemby leveraging pre-trained global Vision Transformer features, which natu-rally captures large displacements. This is followed by a few lightweightiterative refinement to further improve the sub-pixel accuracy. Extensiveexperiments demonstrate that MegaFlow achieves state-of-the-art zero-shot performance across multiple optical flow benchmarks. Moreover, ourmodel also delivers highly competitive zero-shot performance on long-range point tracking benchmarks, demonstrating its robust transferabilityand suggesting a unified paradigm for generalizable motion estimation.Project Page: https://kristen-z.github.io/projects/megaflow/.