Deep Iterative Frame Interpolation for Full-frame Video Stabilization

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Video stabilization is a fundamental and important technique for higher quality videos. Prior works have extensively explored video stabilization, but most of them involve cropping of the frame boundaries and introduce moderate levels of distortion. We present a novel deep approach to video stabilization that can generate video frames without cropping and low distortion. The proposed framework utilizes frame interpolation techniques to generate in between frames, leading to reduced inter-frame jitter. Once applied in an iterative fashion, the stabilization effect becomes stronger. A major advantage is that our framework is end-to-end trainable in an unsupervised manner. In addition, our method is able to run in near real-time (15 fps). To the best of our knowledge, this is the first work to propose an unsupervised deep approach to full-frame video stabilization. We show the advantages of our method through quantitative and qualitative evaluations comparing to the state-of-the-art methods.
Publisher
ASSOC COMPUTING MACHINERY
Issue Date
2020-02
Language
English
Article Type
Article
Citation

ACM TRANSACTIONS ON GRAPHICS, v.39, no.1

ISSN
0730-0301
DOI
10.1145/3363550
URI
http://hdl.handle.net/10203/272266
Appears in Collection
EE-Journal Papers(저널논문)
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