AIM 2019 Challenge on Video Temporal Super-Resolution: Methods and Results

2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW), Seoul, Korea (South), 2019, pp. 3388-3398 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...

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Bibliographic Details
Main Authors Nah, Seungjun, Son, Sanghyun, Timofte, Radu, Lee, Kyoung Mu
Format Journal Article
LanguageEnglish
Published 03.05.2020
Subjects
Computer Science - Computer Vision and Pattern Recognition
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Summary:2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW), Seoul, Korea (South), 2019, pp. 3388-3398 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-framerate (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 superresolution.
DOI:10.48550/arxiv.2005.01233