Search Results for author: Kyung-Ah Sohn

Found 13 papers, 7 papers with code

Decomposing Texture and Semantics for Out-of-distribution Detection

no code implementations29 Sep 2021 Jeong-Hyeon Moon, Namhyuk Ahn, Kyung-Ah Sohn

Out-of-distribution (OOD) detection has made significant progress in recent years because the distribution mismatch between the training and testing can severely deteriorate the reliability of a machine learning system. Nevertheless, the lack of precise interpretation of the in-distribution limits the application of OOD detection methods to real-world system pipielines.

OOD Detection Out-of-Distribution Detection

Dataset Bias Prediction for Few-Shot Image Classification

no code implementations29 Sep 2021 Jangwook Kim, Kyung-Ah Sohn

Once the features are extracted from an image data, the bias prediction network tries to recover the bias of the raw image such as color from the features.

Classification Few-Shot Image Classification

What is Wrong with One-Class Anomaly Detection?

1 code implementation20 Apr 2021 JuneKyu Park, Jeong-Hyeon Moon, Namhyuk Ahn, Kyung-Ah Sohn

From a safety perspective, a machine learning method embedded in real-world applications is required to distinguish irregular situations.

Anomaly Detection

Restoring Spatially-Heterogeneous Distortions using Mixture of Experts Network

1 code implementation30 Sep 2020 Sijin Kim, Namhyuk Ahn, Kyung-Ah Sohn

Viewing in a different point of combining, we introduce a spatially-heterogeneous distortion dataset in which multiple corruptions are applied to the different locations of each image.

Multi-Task Learning

SimUSR: A Simple but Strong Baseline for Unsupervised Image Super-resolution

no code implementations23 Apr 2020 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.

Denoising Image Super-Resolution +1

Efficient Deep Neural Network for Photo-realistic Image Super-Resolution

1 code implementation6 Mar 2019 Namhyuk Ahn, Byungkon Kang, Kyung-Ah Sohn

Recent progress in deep learning-based models has improved photo-realistic (or perceptual) single-image super-resolution significantly.

Image Super-Resolution

Investigating the feature collection for semantic segmentation via single skip connection

no code implementations23 Oct 2017 Jonghwa Yim, Kyung-Ah Sohn

Therefore, in this study, we exhaustively research skip connections of state-of-the-art deep convolutional networks and investigate the characteristics of the features from each intermediate layer.

Object Detection Semantic Segmentation

Enhancing the Performance of Convolutional Neural Networks on Quality Degraded Datasets

no code implementations18 Oct 2017 Jonghwa Yim, Kyung-Ah Sohn

Despite the appeal of deep neural networks that largely replace the traditional handmade filters, they still suffer from isolated cases that cannot be properly handled only by the training of convolutional filters.

Image Classification

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