23 citations · 37 across the 7 of their papers we have counts for
9 papers
WebtoonMe: A Data-Centric Approach for Full-Body Portrait Stylization
Jihye Back, Seungkwon Kim, Namhyuk Ahn
Full-body portrait stylization, which aims to translate portrait photography into a cartoon style, has drawn attention recently. However, most methods have focused only on converti…
Cross-Domain Style Mixing for Face Cartoonization
Seungkwon Kim, Chaeheon Gwak, Dohyun Kim +4
Cartoon domain has recently gained increasing popularity. Previous studies have attempted quality portrait stylization into the cartoon domain; however, this poses a great challeng…
What is Wrong with One-Class Anomaly Detection?
JuneKyu Park, Jeong-Hyeon Moon, Namhyuk Ahn +1
From a safety perspective, a machine learning method embedded in real-world applications is required to distinguish irregular situations. For this reason, there has been a growing…
Restoring Spatially-Heterogeneous Distortions using Mixture of Experts Network
Sijin Kim, Namhyuk Ahn, Kyung-Ah Sohn
In recent years, deep learning-based methods have been successfully applied to the image distortion restoration tasks. However, scenarios that assume a single distortion only may n…
NTIRE 2020 Challenge on Real-World Image Super-Resolution: Methods and Results
Andreas Lugmayr, Martin Danelljan, Radu Timofte +43
This paper reviews the NTIRE 2020 challenge on real world super-resolution. It focuses on the participating methods and final results. The challenge addresses the real world settin…
SimUSR: A Simple but Strong Baseline for Unsupervised Image Super-resolution
Namhyuk Ahn, Jaejun Yoo, Kyung-Ah Sohn
In this paper, we tackle a fully unsupervised super-resolution problem, i.e., neither paired images nor ground truth HR images. We assume that low resolution (LR) images are relati…