23 citations · 70 across the 12 of their papers we have counts for
13 papers
Why Is It Hate Speech? Masked Rationale Prediction for Explainable Hate Speech Detection
Jiyun Kim, Byounghan Lee, Kyung-Ah Sohn
In a hate speech detection model, we should consider two critical aspects in addition to detection performance-bias and explainability. Hate speech cannot be identified based solel…
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…
Rethinking Data Augmentation for Image Super-resolution: A Comprehensive Analysis and a New Strategy
Jaejun Yoo, Namhyuk Ahn, Kyung-Ah Sohn
Data augmentation is an effective way to improve the performance of deep networks. Unfortunately, current methods are mostly developed for high-level vision tasks (e.g., classifica…