Search Results for author: Younghyun Jo

Found 6 papers, 4 papers with code

Practical Single-Image Super-Resolution Using Look-Up Table

1 code implementation CVPR 2021 Younghyun Jo, Seon Joo Kim

We train a deep SR network with a small receptive field and transfer the output values of the learned deep model to the LUT.

Image Super-Resolution

Deep Space-Time Video Upsampling Networks

1 code implementation ECCV 2020 Jaeyeon Kang, Younghyun Jo, Seoung Wug Oh, Peter Vajda, Seon Joo Kim

Video super-resolution (VSR) and frame interpolation (FI) are traditional computer vision problems, and the performance have been improving by incorporating deep learning recently.

Motion Compensation Video Super-Resolution

Deep Video Super-Resolution Network Using Dynamic Upsampling Filters Without Explicit Motion Compensation

1 code implementation CVPR 2018 Younghyun Jo, Seoung Wug Oh, Jaeyeon Kang, Seon Joo Kim

We propose a novel end-to-end deep neural network that generates dynamic upsampling filters and a residual image, which are computed depending on the local spatio-temporal neighborhood of each pixel to avoid explicit motion compensation.

Data Augmentation Motion Compensation +2

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