22 citations · 26 across the 5 of their papers we have counts for
5 papers
Expanded Adaptive Scaling Normalization for End to End Image Compression
Chajin Shin, Hyeongmin Lee, Hanbin Son +3
Recently, learning-based image compression methods that utilize convolutional neural layers have been developed rapidly. Rescaling modules such as batch normalization which are oft…
Exploring Discontinuity for Video Frame Interpolation
Sangjin Lee, Hyeongmin Lee, Chajin Shin +2
Video frame interpolation (VFI) is the task that synthesizes the intermediate frame given two consecutive frames. Most of the previous studies have focused on appropriate frame war…
Smoother Network Tuning and Interpolation for Continuous-level Image Processing
Hyeongmin Lee, Taeoh Kim, Hanbin Son +3
In Convolutional Neural Network (CNN) based image processing, most studies propose networks that are optimized to single-level (or single-objective); thus, they underperform on oth…
Enhanced Standard Compatible Image Compression Framework based on Auxiliary Codec Networks
Hanbin Son, Taeoh Kim, Hyeongmin Lee +1
To enhance image compression performance, recent deep neural network-based research can be divided into three categories: a learnable codec, a postprocessing network, and a compact…
Regularized Adaptation for Stable and Efficient Continuous-Level Learning on Image Processing Networks
Hyeongmin Lee, Taeoh Kim, Hanbin Son +3
In Convolutional Neural Network (CNN) based image processing, most of the studies propose networks that are optimized for a single-level (or a single-objective); thus, they underpe…