Towards Dependable Optical Flow: Benchmarks for Real-World Spatiotemporal Corruptions

Optical flow estimation is a fundamental task in dynamic scene understanding and computer vision. While recent deep models achieve impressive accuracy on clean benchmarks, their robustness to common visual and temporal degradations remains insufficiently explored. To address this gap, we establish a