181 citations · 377 across the 11 of their papers we have counts for
12 papers
Deep Deformable 3D Caricatures with Learned Shape Control
Yucheol Jung, Wonjong Jang, Soongjin Kim +3
A 3D caricature is an exaggerated 3D depiction of a human face. The goal of this paper is to model the variations of 3D caricatures in a compact parameter space so that we can prov…
Real-Time Video Deblurring via Lightweight Motion Compensation
Hyeongseok Son, Junyong Lee, Sunghyun Cho +1
While motion compensation greatly improves video deblurring quality, separately performing motion compensation and video deblurring demands huge computational overhead. This paper…
Reference-based Video Super-Resolution Using Multi-Camera Video Triplets
Junyong Lee, Myeonghee Lee, Sunghyun Cho +1
We propose the first reference-based video super-resolution (RefVSR) approach that utilizes reference videos for high-fidelity results. We focus on RefVSR in a triple-camera settin…
MSSNet: Multi-Scale-Stage Network for Single Image Deblurring
Kiyeon Kim, Seungyong Lee, Sunghyun Cho
Most of traditional single image deblurring methods before deep learning adopt a coarse-to-fine scheme that estimates a sharp image at a coarse scale and progressively refines it a…
Realistic Blur Synthesis for Learning Image Deblurring
Jaesung Rim, Geonung Kim, Jungeon Kim +3
Training learning-based deblurring methods demands a tremendous amount of blurred and sharp image pairs. Unfortunately, existing synthetic datasets are not realistic enough, and de…
Recurrent Video Deblurring with Blur-Invariant Motion Estimation and Pixel Volumes
Hyeongseok Son, Junyong Lee, Jonghyeop Lee +2
For the success of video deblurring, it is essential to utilize information from neighboring frames. Most state-of-the-art video deblurring methods adopt motion compensation betwee…
Single Image Defocus Deblurring Using Kernel-Sharing Parallel Atrous Convolutions
Hyeongseok Son, Junyong Lee, Sunghyun Cho +1
This paper proposes a novel deep learning approach for single image defocus deblurring based on inverse kernels. In a defocused image, the blur shapes are similar among pixels alth…
Spatiotemporal Texture Reconstruction for Dynamic Objects Using a Single RGB-D Camera
Hyomin Kim, Jungeon Kim, Hyeonseo Nam +2
This paper presents an effective method for generating a spatiotemporal (time-varying) texture map for a dynamic object using a single RGB-D camera. The input of our framework is a…
Deep Virtual Markers for Articulated 3D Shapes
Hyomin Kim, Jungeon Kim, Jaewon Kam +2
We propose deep virtual markers, a framework for estimating dense and accurate positional information for various types of 3D data. We design a concept and construct a framework th…
Iterative Filter Adaptive Network for Single Image Defocus Deblurring
Junyong Lee, Hyeongseok Son, Jaesung Rim +2
We propose a novel end-to-end learning-based approach for single image defocus deblurring. The proposed approach is equipped with a novel Iterative Filter Adaptive Network (IFAN) t…
StyleCariGAN: Caricature Generation via StyleGAN Feature Map Modulation
Wonjong Jang, Gwangjin Ju, Yucheol Jung +3
We present a caricature generation framework based on shape and style manipulation using StyleGAN. Our framework, dubbed StyleCariGAN, automatically creates a realistic and detaile…
NPRportrait 1.0: A Three-Level Benchmark for Non-Photorealistic Rendering of Portraits
Paul L. Rosin, Yu-Kun Lai, David Mould +10
Despite the recent upsurge of activity in image-based non-photorealistic rendering (NPR), and in particular portrait image stylisation, due to the advent of neural style transfer,…