MIORe & VAR-MIORe: Benchmarks to Push the Boundaries of Restoration
George Ciubotariu, Zhuyun Zhou, Zongwei Wu, Radu Timofte
Abstract
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 depthdependent 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.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext 5f68366b-c61f-4aa1-9a48-a6d24c5f0963Builds on16
- Human-Aware Motion DeblurringZiyi Shen, Wenguan Wang, Xiankai Lu, Jianbing Shen et al.ICCV 2019 · 374 citations
- XVFI: eXtreme Video Frame InterpolationHyeonjun Sim, Jihyong Oh, Munchurl KimICCV 2021 · 207 citations
- VideoFlow: Exploiting Temporal Cues for Multi-frame Optical Flow EstimationXiaoyu Shi, Zhaoyang Huang, Weikang Bian, Dasong Li et al.ICCV 2023 · 112 citations
- Blind Image Super-resolution with Elaborate Degradation Modeling on Noise and KernelZongsheng Yue, Qian Zhao, Jianwen Xie, Lei Zhang et al.CVPR 2022 · 76 citations
- VFIMamba: Video Frame Interpolation with State Space ModelsGuozhen Zhang, Chunxu Liu, Yutao Cui, Xiaotong Zhao et al.NeurIPS 2024 · 48 citations
Related papers
- OMoBlur: An Object Motion Blur Dataset and Benchmark for Real-World Local Motion DeblurringDingchuan Yu, Jiatong Li, Jingwen Zhou, Zhengyue Zhuge et al.CVPR 2026 · 1 citation
- Event-Based Frame Interpolation with Ad-hoc DeblurringLei Sun, Christos Sakaridis, Jingyun Liang, Peng Sun et al.CVPR 2023
- Towards Rolling Shutter Correction and Deblurring in Dynamic ScenesZhihang Zhong, Yinqiang Zheng, Imari SatoCVPR 2021
- Spring: A High-Resolution High-Detail Dataset and Benchmark for Scene Flow, Optical Flow and StereoLukas Mehl, Jenny Schmalfuss, Azin Jahedi, Yaroslava Nalivayko et al.CVPR 2023
- ARVo: Learning All-Range Volumetric Correspondence for Video DeblurringDongxu Li, Chenchen Xu, Kaihao Zhang, Xin Yu et al.CVPR 2021
