MIORe & VAR-MIORe: Benchmarks to Push the Boundaries of Restoration
Not on the map. Why?
Abstract (arXiv)
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.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 22 of its 33 references that are in the map. First posted on arXiv 8 Sep 2025.
Builds on
22 of 33 references.
References · 22
- 2015FlowNet: Learning Optical Flow with Convolutional Networkscited by 1,059
- 2015A Large Dataset to Train Convolutional Networks for Disparity, Optical Flow, and Scene Flow Estimationcited by 881
- 2016Deep Multi-scale Convolutional Neural Network for Dynamic Scene Deblurringcited by 727
- 2022Simple Baselines for Image Restorationcited by 708
- 2017Video Enhancement with Task-Oriented Flowcited by 619
- 2022FlowFormer: A Transformer Architecture for Optical Flowcited by 275
- 2020Human-Aware Motion Deblurringcited by 175
- 2022Efficient Frequency Domain-based Transformers for High-Quality Image Deblurringcited by 165
- 2023BiFormer: Vision Transformer with Bi-Level Routing Attentioncited by 151
- 2021XVFI: eXtreme Video Frame Interpolationcited by 126
- 2023Extracting Motion and Appearance via Inter-Frame Attention for Efficient Video Frame Interpolationcited by 98
- 2023VideoFlow: Exploiting Temporal Cues for Multi-frame Optical Flow Estimationcited by 82
10 more
- 2022Deep Equilibrium Optical Flow Estimationcited by 64
- 2024MemFlow: Optical Flow Estimation and Prediction with Memorycited by 55
- 2024Sparse Global Matching for Video Frame Interpolation with Large Motioncited by 28
- 2021Blind Image Super-resolution with Elaborate Degradation Modeling on Noise and Kernelcited by 27
- 2024AdaRevD: Adaptive Patch Exiting Reversible Decoder Pushes the Limit of Image Deblurringcited by 25
- 2024Perception-Oriented Video Frame Interpolation via Asymmetric Blendingcited by 23
- 2022A Closer Look at Blind Super-Resolution: Degradation Models, Baselines, and Performance Upper Boundscited by 22
- 2024VFIMamba: Video Frame Interpolation with State Space Modelscited by 22
- 2024LoFormer: Local Frequency Transformer for Image Deblurringcited by 20
- 2024Rethinking RAFT for Efficient Optical Flowcited by 8
Built on by
Citing papers per year: 2026: 2.
2 papers.