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Harnessing Meta-Learning for Improving Full-Frame Video Stabilization
March 7, 2024, 5:45 a.m. | Muhammad Kashif Ali, Eun Woo Im, Dongjin Kim, Tae Hyun Kim
cs.CV updates on arXiv.org arxiv.org
Abstract: Video stabilization is a longstanding computer vision problem, particularly pixel-level synthesis solutions for video stabilization which synthesize full frames add to the complexity of this task. These techniques aim to stabilize videos by synthesizing full frames while enhancing the stability of the considered video. This intensifies the complexity of the task due to the distinct mix of unique motion profiles and visual content present in each video sequence, making robust generalization with fixed parameters difficult. …
abstract aim arxiv complexity computer computer vision cs.cv meta meta-learning pixel solutions stability synthesis type video videos vision
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