no code implementations • 6 May 2022 • Jeong-gi Kwak, Yuanming Li, Dongsik Yoon, David Han, Hanseok Ko
Although the progress of generative models enables the stylization of a portrait, obtaining the stylized image in canonical view is still a challenging task.
no code implementations • 3 May 2022 • Donghyeon Kim, Gwantae Kim, Bokyeung Lee, Jeong-gi Kwak, David K. Han, Hanseok Ko
However, the performance of the dynamic filter might be degraded since simple feature pooling is used to reduce the computational resource in the IDF part.
1 code implementation • 8 Dec 2021 • Jeong-gi Kwak, Youngsaeng Jin, Yuanming Li, Dongsik Yoon, Donghyeon Kim, Hanseok Ko
To address this issue, we propose a novel GAN model, i. e., AU-GAN, which has an asymmetric architecture for adverse domain translation.
no code implementations • 19 Nov 2021 • Han Chen, Yifan Jiang, Hanseok Ko
Due to the fast processing-speed and robustness it can achieve, skeleton-based action recognition has recently received the attention of the computer vision community.
no code implementations • 13 Oct 2021 • Han Chen, Yifan Jiang, Hanseok Ko, Murray Loew
Automatic segmentation of infected regions in computed tomography (CT) images is necessary for the initial diagnosis of COVID-19.
no code implementations • 23 Sep 2021 • Donghyeon Kim, Kyungdeuk Ko, Jeong-gi Kwak, David K. Han, Hanseok Ko
This lightweight dynamic filter is applied to the front-end of KWS to enhance the separability of the input data.
1 code implementation • 16 Aug 2021 • Ange Lou, Shuyue Guan, Hanseok Ko, Murray Loew
Segmenting medical images accurately and reliably is important for disease diagnosis and treatment.
Ranked #3 on
Medical Image Segmentation
on ETIS-LARIBPOLYPDB
1 code implementation • 12 Aug 2021 • Youngsaeng Jin, David K. Han, Hanseok Ko
In this paper, a built-in memory module for semantic segmentation is proposed to overcome these problems.
no code implementations • 10 Aug 2021 • Youngsaeng Jin, Jonghwan Hong, David Han, Hanseok Ko
Anomaly detection in video streams is a challenging problem because of the scarcity of abnormal events and the difficulty of accurately annotating them.
no code implementations • 1 Feb 2021 • Yifan Jiang, Han Chen, David K. Han, Hanseok Ko
To compensate for the sparseness of labeled data, the proposed method utilizes a large amount of synthetic COVID-19 CT images and adjusts the networks from the source domain (synthetic data) to the target domain (real data) with a cross-domain training mechanism.
1 code implementation • ECCV 2020 • Jeong-gi Kwak, David K. Han, Hanseok Ko
The goal of face attribute editing is altering a facial image according to given target attributes such as hair color, mustache, gender, etc.
no code implementations • 23 Nov 2020 • Han Chen, Yifan Jiang, Murray Loew, Hanseok Ko
In this paper, we propose an unsupervised domain adaptation based segmentation network to improve the segmentation performance of the infection areas in COVID-19 CT images.
no code implementations • 29 Jul 2020 • Yifan Jiang, Han Chen, Murray Loew, Hanseok Ko
However, training a deep-learning model requires large volumes of data, and medical staff faces a high risk when collecting COVID-19 CT data due to the high infectivity of the disease.
1 code implementation • 27 May 2020 • Shuyue Guan, Murray Loew, Hanseok Ko
In machine learning, the performance of a classifier depends on both the classifier model and the dataset.
5 code implementations • 5 May 2020 • Andreas Lugmayr, Martin Danelljan, Radu Timofte, Namhyuk Ahn, Dongwoon Bai, Jie Cai, Yun Cao, Junyang Chen, Kaihua Cheng, SeYoung Chun, Wei Deng, Mostafa El-Khamy, Chiu Man Ho, Xiaozhong Ji, Amin Kheradmand, Gwantae Kim, Hanseok Ko, Kanghyu Lee, Jungwon Lee, Hao Li, Ziluan Liu, Zhi-Song Liu, Shuai Liu, Yunhua Lu, Zibo Meng, Pablo Navarrete Michelini, Christian Micheloni, Kalpesh Prajapati, Haoyu Ren, Yong Hyeok Seo, Wan-Chi Siu, Kyung-Ah Sohn, Ying Tai, Rao Muhammad Umer, Shuangquan Wang, Huibing Wang, Timothy Haoning Wu, Hao-Ning Wu, Biao Yang, Fuzhi Yang, Jaejun Yoo, Tongtong Zhao, Yuanbo Zhou, Haijie Zhuo, Ziyao Zong, Xueyi Zou
This paper reviews the NTIRE 2020 challenge on real world super-resolution.
no code implementations • 26 Jul 2019 • Alzahra Badi, Sangwook Park, David K. Han, Hanseok Ko
Performance of learning based Automatic Speech Recognition (ASR) is susceptible to noise, especially when it is introduced in the testing data while not presented in the training data.
no code implementations • 7 Jan 2019 • Sangwook Park, David K. Han, Hanseok Ko
Audio waveform generation can then be performed using the proposed network.
no code implementations • 3 Feb 2017 • Suwon Shon, Hanseok Ko
As development dataset which is spoken in Cebuano and Mandarin, we could prepare the evaluation trials through preliminary experiments to compensate the language mismatched condition.
no code implementations • 21 Sep 2016 • Suwon Shon, Seongkyu Mun, John H. L. Hansen, Hanseok Ko
The experimental results show that the use of duration and score fusion improves language recognition performance by 5% relative in LRiMLC15 cost.