What is it about?
Video Frame Interpolation (VFI) is a fascinating and challenging problem in the computer vision (CV) field, aiming to generate non-existing frames between two consecutive video frames. In recent years, many algorithms based on optical flow, kernel, or phase information have been proposed. In this paper, we provide a comprehensive review of recent developments in the VFI technique.
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Why is it important?
We introduce the history of VFI algorithms’ development, the evaluation metrics, and publicly available datasets. We compare each algorithm in detail, point out their advantages and disadvantages, and compare their interpolation performance and speed on different remarkable datasets. VFI technology has arisen continuous attention in the CV community, some video processing applications based on VFI are also mentioned in this survey, such as slow-motion generation, video compression, and video restoration.
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This page is a summary of: Video Frame Interpolation: A Comprehensive Survey, ACM Transactions on Multimedia Computing Communications and Applications, January 2023, ACM (Association for Computing Machinery), DOI: 10.1145/3556544.
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