A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf
.
Learning to Extract Flawless Slow Motion From Blurry Videos
2019
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
In this paper, we introduce the task of generating a sharp slow-motion video given a low frame rate blurry video. We propose a data-driven approach, where the training data is captured with a high frame rate camera and blurry images are simulated through an averaging process. While it is possible to train a neural network to recover the sharp frames from their average, there is no guarantee of the temporal smoothness for the formed video, as the frames are estimated independently. To address
doi:10.1109/cvpr.2019.00830
dblp:conf/cvpr/JinHF19
fatcat:gpbb5hkdxncz3etik3staxcupm