AIM 2019 Challenge on Video Temporal Super-Resolution: Methods and Results
Abstract
Videos contain various types and strengths of motions that may look unnaturally discontinuous in time when the recorded frame rate is low. This paper reviews the first AIM challenge on video temporal super-resolution (frame interpolation) with a focus on the proposed solutions and results. From low-frame-rate (15 fps) video sequences, the challenge participants are asked to submit higher-frame-rate (60 fps) video sequences by estimating temporally intermediate frames. We employ the REDS_VTSR dataset derived from diverse videos captured in a hand-held camera for training and evaluation purposes. The competition had 62 registered participants, and a total of 8 teams competed in the final testing phase. The challenge winning methods achieve the state-of-the-art in video temporal super-resolution.
Cite
Text
Nah et al. "AIM 2019 Challenge on Video Temporal Super-Resolution: Methods and Results." IEEE/CVF International Conference on Computer Vision Workshops, 2019. doi:10.1109/ICCVW.2019.00421Markdown
[Nah et al. "AIM 2019 Challenge on Video Temporal Super-Resolution: Methods and Results." IEEE/CVF International Conference on Computer Vision Workshops, 2019.](https://mlanthology.org/iccvw/2019/nah2019iccvw-aim/) doi:10.1109/ICCVW.2019.00421BibTeX
@inproceedings{nah2019iccvw-aim,
title = {{AIM 2019 Challenge on Video Temporal Super-Resolution: Methods and Results}},
author = {Nah, Seungjun and Kim, Heewon and Han, Bohyung and Xu, Ning and Park, Bumjun and Yu, Songhyun and Kim, Sangmin and Jeong, Jechang and Shen, Wang and Bao, Wenbo and Zhai, Guangtao and Son, Sanghyun and Chen, Li and Gao, Zhiyong and Chen, Guannan and Lu, Yunhua and Duan, Ran and Liu, Tong and Zhang, Lijie and Park, Woon-Sung and Kim, Munchurl and Pisha, George and Timofte, Radu and Naor, Eyal and Aloni, Lior and Lee, Kyoung Mu and Siyao, Li and Pan, Ze and Xu, Xiangyu and Sun, Wenxiu and Choi, Myungsub},
booktitle = {IEEE/CVF International Conference on Computer Vision Workshops},
year = {2019},
pages = {3388-3398},
doi = {10.1109/ICCVW.2019.00421},
url = {https://mlanthology.org/iccvw/2019/nah2019iccvw-aim/}
}