English

Blurry Video Frame Interpolation

Computer Vision and Pattern Recognition 2020-02-28 v1

Abstract

Existing works reduce motion blur and up-convert frame rate through two separate ways, including frame deblurring and frame interpolation. However, few studies have approached the joint video enhancement problem, namely synthesizing high-frame-rate clear results from low-frame-rate blurry inputs. In this paper, we propose a blurry video frame interpolation method to reduce motion blur and up-convert frame rate simultaneously. Specifically, we develop a pyramid module to cyclically synthesize clear intermediate frames. The pyramid module features adjustable spatial receptive field and temporal scope, thus contributing to controllable computational complexity and restoration ability. Besides, we propose an inter-pyramid recurrent module to connect sequential models to exploit the temporal relationship. The pyramid module integrates a recurrent module, thus can iteratively synthesize temporally smooth results without significantly increasing the model size. Extensive experimental results demonstrate that our method performs favorably against state-of-the-art methods.

Cite

@article{arxiv.2002.12259,
  title  = {Blurry Video Frame Interpolation},
  author = {Wang Shen and Wenbo Bao and Guangtao Zhai and Li Chen and Xiongkuo Min and Zhiyong Gao},
  journal= {arXiv preprint arXiv:2002.12259},
  year   = {2020}
}

Comments

This work is accepted in CVPR 2020

R2 v1 2026-06-23T13:56:28.476Z