Moment-Reenacting: Inverse Motion Degradation with Cross-shutter Guidance

• URL: http://arxiv.org/abs/2605.22423v2
• Date: Fri, 22 May 2026 03:42:26 GMT
• Title: Moment-Reenacting: Inverse Motion Degradation with Cross-shutter Guidance
• Abstract summary: We propose a unified framework to invert motion degradation and reenact imaging moment.<n>We introduce a novel dual-shutter setup that captures synchronized blur-RS image pairs.<n>For allowing flexible performance-cost trade-offs, we extend this dual-shutter setup to a stereo Blur-RS configuration.
• Score: 38.2932325938093
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Motion degradation, manifested as blur in global shutter (GS) images or rolling shutter (RS) distortion in RS counterparts, remains a fundamental challenge in computational imaging, especially under fast motion or low-light conditions. While prior works have treated blur decomposition and RS temporal super-resolution as separate tasks, this separation fails to exploit their intrinsic complementarity. In this paper, we propose a unified framework to invert motion degradation and reenact imaging moment by jointly leveraging the complementary characteristics of GS blur and RS distortion. To this end, we introduce a novel dual-shutter setup that captures synchronized blur-RS image pairs and demonstrate that this combination effectively resolves temporal and spatial ambiguities inherent in both modalities. For allowing flexible performance-cost trade-offs, we further extend this dual-shutter setup to a stereo Blur-RS configuration with a narrow baseline. In addition, we construct a triaxial imaging system to collect a real-world dataset with aligned GS-RS pairs and ground-truth high-speed frames, enabling robust training and evaluation beyond synthetic data. Our proposed network explicitly disentangles motion into context-aware and temporally-sensitive representations via a dual-stream motion interpretation module, followed by a self-prompted frame reconstruction stage. Extensive experiments validate the superiority and generalizability of our approach, establishing a new paradigm for realistic high-speed video reconstruction under complex motion degradations. Codes and more resources are available at https://jixiang2016.github.io/dualBR_site/.

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