MIORe & VAR-MIORe: Benchmarks to Push the Boundaries of Restoration
This provides domain-specific benchmarks for image and video restoration research, though it is incremental as it builds on existing benchmark concepts.
The authors tackled limitations in motion restoration benchmarks by introducing MIORe and VAR-MIORe, two multi-task datasets with high-frame-rate acquisition and professional-grade optics that capture diverse motion scenarios, resulting in scalable ground truths that challenge existing algorithms.
We introduce MIORe and VAR-MIORe, two novel multi-task datasets that address critical limitations in current motion restoration benchmarks. Designed with high-frame-rate (1000 FPS) acquisition and professional-grade optics, our datasets capture a broad spectrum of motion scenarios, which include complex ego-camera movements, dynamic multi-subject interactions, and depth-dependent blur effects. By adaptively averaging frames based on computed optical flow metrics, MIORe generates consistent motion blur, and preserves sharp inputs for video frame interpolation and optical flow estimation. VAR-MIORe further extends by spanning a variable range of motion magnitudes, from minimal to extreme, establishing the first benchmark to offer explicit control over motion amplitude. We provide high-resolution, scalable ground truths that challenge existing algorithms under both controlled and adverse conditions, paving the way for next-generation research of various image and video restoration tasks.