AIM 2019 Challenge on Video Temporal Super-Resolution: Methods and
Results
- URL: http://arxiv.org/abs/2005.01233v1
- Date: Mon, 4 May 2020 01:51:23 GMT
- Title: AIM 2019 Challenge on Video Temporal Super-Resolution: Methods and
Results
- Authors: Seungjun Nah, Sanghyun Son, Radu Timofte and Kyoung Mu Lee
- Abstract summary: This paper reviews the first AIM challenge on video temporal super-resolution (frame)
From low-frame-rate (15 fps) video sequences, the challenge participants are asked to submit higher-framerate (60 fps) video sequences.
We employ the REDS VTSR dataset derived from diverse videos captured in a hand-held camera for training and evaluation purposes.
- Score: 129.15554076593762
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- 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-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.
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