6 citations · 6 across the 1 of their papers we have counts for
5 papers
KOALAnet: Blind Super-Resolution using Kernel-Oriented Adaptive Local Adjustment
Soo Ye Kim, Hyeonjun Sim, Munchurl Kim
Blind super-resolution (SR) methods aim to generate a high quality high resolution image from a low resolution image containing unknown degradations. However, natural images contai…
JSI-GAN: GAN-Based Joint Super-Resolution and Inverse Tone-Mapping with Pixel-Wise Task-Specific Filters for UHD HDR Video
Soo Ye Kim, Jihyong Oh, Munchurl Kim
Joint learning of super-resolution (SR) and inverse tone-mapping (ITM) has been explored recently, to convert legacy low resolution (LR) standard dynamic range (SDR) videos to high…
Single Image Reflection Removal with Physically-Based Training Images
Soomin Kim, Yuchi Huo, Sung-Eui Yoon
Recently, deep learning-based single image reflection separation methods have been exploited widely. To benefit the learning approach, a large number of training image pairs (i.e.,…
Deep SR-ITM: Joint Learning of Super-Resolution and Inverse Tone-Mapping for 4K UHD HDR Applications
Soo Ye Kim, Jihyong Oh, Munchurl Kim
Recent modern displays are now able to render high dynamic range (HDR), high resolution (HR) videos of up to 8K UHD (Ultra High Definition). Consequently, UHD HDR broadcasting and…
3DSRnet: Video Super-resolution using 3D Convolutional Neural Networks
Soo Ye Kim, Jeongyeon Lim, Taeyoung Na +1
In video super-resolution, the spatio-temporal coherence between, and among the frames must be exploited appropriately for accurate prediction of the high resolution frames. Althou…