AIM 2020 Challenge on Video Temporal Super-Resolution
This work addresses the problem of unnatural video playback due to low frame rates for video processing researchers, but it is incremental as it builds on existing frame interpolation challenges.
The paper reports on the AIM 2020 Challenge on Video Temporal Super-Resolution, where participants aimed to increase frame rates from 15 fps to 30 or 60 fps using the REDS_VTSR dataset, with the winning team achieving state-of-the-art results through an enhanced quadratic video interpolation method.
Videos in the real-world contain various dynamics and motions that may look unnaturally discontinuous in time when the recordedframe rate is low. This paper reports the second AIM challenge on Video Temporal Super-Resolution (VTSR), a.k.a. frame interpolation, with a focus on the proposed solutions, results, and analysis. From low-frame-rate (15 fps) videos, the challenge participants are required to submit higher-frame-rate (30 and 60 fps) sequences by estimating temporally intermediate frames. To simulate realistic and challenging dynamics in the real-world, we employ the REDS_VTSR dataset derived from diverse videos captured in a hand-held camera for training and evaluation purposes. There have been 68 registered participants in the competition, and 5 teams (one withdrawn) have competed in the final testing phase. The winning team proposes the enhanced quadratic video interpolation method and achieves state-of-the-art on the VTSR task.