English

AIM 2020 Challenge on Video Temporal Super-Resolution

Computer Vision and Pattern Recognition 2020-09-29 v1

Abstract

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 There have been 68 registered participants in the competition, and 5 teams (one withdrawn) have competed in the final testing phase.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.

Keywords

Cite

@article{arxiv.2009.12987,
  title  = {AIM 2020 Challenge on Video Temporal Super-Resolution},
  author = {Sanghyun Son and Jaerin Lee and Seungjun Nah and Radu Timofte and Kyoung Mu Lee},
  journal= {arXiv preprint arXiv:2009.12987},
  year   = {2020}
}

Comments

Published in ECCV 2020 Workshop (Advances in Image Manipulation)

R2 v1 2026-06-23T18:49:53.217Z