19 citations · 29 across the 5 of their papers we have counts for
12 papers
Restore from Restored: Single-image Inpainting
Eunhye Lee, Jeongmu Kim, Jisu Kim +1
Recent image inpainting methods have shown promising results due to the power of deep learning, which can explore external information available from the large training dataset. Ho…
Restore from Restored: Single-image Inpainting
Eunhye Lee, Jeongmu Kim, Jisu Kim +1
Recent image inpainting methods show promising results due to the power of deep learning, which can explore external information available from a large training dataset. However, m…
Self-Supervised Adaptation for Video Super-Resolution
Jinsu Yoo, Tae Hyun Kim
Recent single-image super-resolution (SISR) networks, which can adapt their network parameters to specific input images, have shown promising results by exploiting the information…
Deep Motion Blind Video Stabilization
Muhammad Kashif Ali, Sangjoon Yu, Tae Hyun Kim
Despite the advances in the field of generative models in computer vision, video stabilization still lacks a pure regressive deep-learning-based formulation. Deep video stabilizati…
Scene-Adaptive Video Frame Interpolation via Meta-Learning
Myungsub Choi, Janghoon Choi, Sungyong Baik +2
Video frame interpolation is a challenging problem because there are different scenarios for each video depending on the variety of foreground and background motion, frame rate, an…
Restore from Restored: Single Image Denoising with Pseudo Clean Image
Seunghwan Lee, Dongkyu Lee, Donghyeon Cho +2
In this study, we propose a simple and effective fine-tuning algorithm called "restore-from-restored", which can greatly enhance the performance of fully pre-trained image denoisin…