论文标题
VESR-NET：YOUKU视频增强和超分辨率挑战的获胜解决方案
VESR-Net: The Winning Solution to Youku Video Enhancement and Super-Resolution Challenge
论文作者
论文摘要
本文介绍了VESR-NET，这是一种视频增强和超分辨率（VESR）的方法。我们设计了一个单独的非本地模块，以有效地探索视频框架和融合视频帧之间的关系，以及一个频道注意残留块，以捕获VESR-NET中视频框架重建的特征图之间的关系。我们进行了实验，以分析VESR-NET中这些设计的有效性，这证明了VESR-NET比以前最先进的VESR方法的优势。值得一提的是，在超过成千上万的YOUKU视频增强和超级分辨率（Youku-Vesr）挑战中，我们拟议的VESR-NET击败了其他竞争方法，并排名第一。
This paper introduces VESR-Net, a method for video enhancement and super-resolution (VESR). We design a separate non-local module to explore the relations among video frames and fuse video frames efficiently, and a channel attention residual block to capture the relations among feature maps for video frame reconstruction in VESR-Net. We conduct experiments to analyze the effectiveness of these designs in VESR-Net, which demonstrates the advantages of VESR-Net over previous state-of-the-art VESR methods. It is worth to mention that among more than thousands of participants for Youku video enhancement and super-resolution (Youku-VESR) challenge, our proposed VESR-Net beat other competitive methods and ranked the first place.
