ReMATF proposes a lightweight recurrent multi-scale network for atmospheric turbulence mitigation in dynamic videos that uses two-frame recurrent processing with motion-adaptive per-pixel fusion to enhance efficiency and coherence.
In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
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ReMATF: Recurrent Motion-Adaptive Multi-scale Turbulence Mitigation for Dynamic Scenes
ReMATF proposes a lightweight recurrent multi-scale network for atmospheric turbulence mitigation in dynamic videos that uses two-frame recurrent processing with motion-adaptive per-pixel fusion to enhance efficiency and coherence.