MultiBoot Vsr: Multi-Stage Multi-Reference Bootstrapping for Video Super-Resolution

Ratheesh Kalarot, Fatih Porikli
2019 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)  
To make the best use of the previous estimations and shared redundancy across the consecutive video frames, here we propose a scene and class agnostic, fully convolutional neural network model for 4× video super-resolution. One stage of our network is composed of a motion compensation based input subnetwork, a blending backbone, and a spatial upsampling subnetwork. We recurrently apply this network to reconstruct high-resolution frames and then reuse them as additional reference frames after
more » ... huffling them into multiple low-resolution images. This allows us to bootstrap and enhance image quality progressively. Our experiments show that our method generates temporally consistent and high-quality results without artifacts. Our method is ranked as the second best based on the SSIM scores on the NTIRE2019 VSR Challenge, Clean Track.
doi:10.1109/cvprw.2019.00258 dblp:conf/cvpr/KalarotP19 fatcat:44mzymchgzdxlo53s23tlczogq