Scene-Adaptive Video Frame Interpolation via Meta-Learning
- Authors
- Choi, Myungsub; Choi, Janghoon; Baik, Sungyong; Kim, Tae Hyun; Lee, Kyoung Mu
- Issue Date
- Jun-2020
- Publisher
- IEEE Computer Society
- Citation
- Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp.9441 - 9450
- Indexed
- SCOPUS
- Journal Title
- Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
- Start Page
- 9441
- End Page
- 9450
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/145498
- DOI
- 10.1109/CVPR42600.2020.00946
- ISSN
- 1063-6919
- Abstract
- Video frame interpolation is a challenging problem because there are different scenarios for each video depending on the variety of foreground and background motion, frame rate, and occlusion. It is therefore difficult for a single network with fixed parameters to generalize across different videos. Ideally, one could have a different network for each scenario, but this is computationally infeasible for practical applications. In this work, we propose to adapt the model to each video by making use of additional information that is readily available at test time and yet has not been exploited in previous works. We first show the benefits of 'test-time adaptation' through simple fine-tuning of a network, then we greatly improve its efficiency by incorporating meta-learning. We obtain significant performance gains with only a single gradient update without any additional parameters. Finally, we show that our meta-learning framework can be easily employed to any video frame interpolation network and can consistently improve its performance on multiple benchmark datasets.
- Files in This Item
-
Go to Link
- Appears in
Collections - 서울 공과대학 > 서울 컴퓨터소프트웨어학부 > 1. Journal Articles
![qrcode](https://api.qrserver.com/v1/create-qr-code/?size=55x55&data=https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/145498)
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.