42 citations · 77 across the 10 of their papers we have counts for
10 papers
Modernizing Old Photos Using Multiple References via Photorealistic Style Transfer
Agus Gunawan, Soo Ye Kim, Hyeonjun Sim +2
This paper firstly presents old photo modernization using multiple references by performing stylization and enhancement in a unified manner. In order to modernize old photos, we pr…
ObjectStitch: Generative Object Compositing
Yizhi Song, Zhifei Zhang, Zhe Lin +5
Object compositing based on 2D images is a challenging problem since it typically involves multiple processing stages such as color harmonization, geometry correction and shadow ge…
Layered Depth Refinement with Mask Guidance
Soo Ye Kim, Jianming Zhang, Simon Niklaus +4
Depth maps are used in a wide range of applications from 3D rendering to 2D image effects such as Bokeh. However, those predicted by single image depth estimation (SIDE) models oft…
Zoom-to-Inpaint: Image Inpainting with High-Frequency Details
Soo Ye Kim, Kfir Aberman, Nori Kanazawa +6
Although deep learning has enabled a huge leap forward in image inpainting, current methods are often unable to synthesize realistic high-frequency details. In this paper, we propo…
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…
FISR: Deep Joint Frame Interpolation and Super-Resolution with a Multi-scale Temporal Loss
Soo Ye Kim, Jihyong Oh, Munchurl Kim
Super-resolution (SR) has been widely used to convert low-resolution legacy videos to high-resolution (HR) ones, to suit the increasing resolution of displays (e.g. UHD TVs). Howev…
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…