Get our free extension to see links to code for papers anywhere online!

Add to Chrome

Add to Firefox

Picture for Se Young Chun

Se Young Chun

Efficient and Accurate Quantized Image Super-Resolution on Mobile NPUs, Mobile AI & AIM 2022 challenge: Report

Nov 07, 2022
Andrey Ignatov, Radu Timofte, Maurizio Denna, Abdel Younes, Ganzorig Gankhuyag, Jingang Huh, Myeong Kyun Kim, Kihwan Yoon, Hyeon-Cheol Moon, Seungho Lee, Yoonsik Choe, Jinwoo Jeong, Sungjei Kim, Maciej Smyl, Tomasz Latkowski, Pawel Kubik, Michal Sokolski, Yujie Ma, Jiahao Chao, Zhou Zhou, Hongfan Gao, Zhengfeng Yang, Zhenbing Zeng, Zhengyang Zhuge, Chenghua Li, Dan Zhu, Mengdi Sun, Ran Duan, Yan Gao, Lingshun Kong, Long Sun, Xiang Li, Xingdong Zhang, Jiawei Zhang, Yaqi Wu, Jinshan Pan, Gaocheng Yu, Jin Zhang, Feng Zhang, Zhe Ma, Hongbin Wang, Hojin Cho, Steve Kim, Huaen Li, Yanbo Ma, Ziwei Luo, Youwei Li, Lei Yu, Zhihong Wen, Qi Wu, Haoqiang Fan, Shuaicheng Liu, Lize Zhang, Zhikai Zong, Jeremy Kwon, Junxi Zhang, Mengyuan Li, Nianxiang Fu, Guanchen Ding, Han Zhu, Zhenzhong Chen, Gen Li, Yuanfan Zhang, Lei Sun, Dafeng Zhang, Neo Yang, Fitz Liu, Jerry Zhao, Mustafa Ayazoglu, Bahri Batuhan Bilecen, Shota Hirose, Kasidis Arunruangsirilert, Luo Ao, Ho Chun Leung, Andrew Wei, Jie Liu, Qiang Liu, Dahai Yu, Ao Li, Lei Luo, Ce Zhu, Seongmin Hong, Dongwon Park, Joonhee Lee, Byeong Hyun Lee, Seunggyu Lee, Se Young Chun, Ruiyuan He, Xuhao Jiang, Haihang Ruan, Xinjian Zhang, Jing Liu, Garas Gendy, Nabil Sabor, Jingchao Hou, Guanghui He

Figure 1 for Efficient and Accurate Quantized Image Super-Resolution on Mobile NPUs, Mobile AI & AIM 2022 challenge: Report

Figure 2 for Efficient and Accurate Quantized Image Super-Resolution on Mobile NPUs, Mobile AI & AIM 2022 challenge: Report

Figure 3 for Efficient and Accurate Quantized Image Super-Resolution on Mobile NPUs, Mobile AI & AIM 2022 challenge: Report

Figure 4 for Efficient and Accurate Quantized Image Super-Resolution on Mobile NPUs, Mobile AI & AIM 2022 challenge: Report

* arXiv admin note: text overlap with arXiv:2105.07825, arXiv:2105.08826, arXiv:2211.04470, arXiv:2211.03885, arXiv:2211.05256

Access Paper or Ask Questions

Efficient Single-Image Depth Estimation on Mobile Devices, Mobile AI & AIM 2022 Challenge: Report

Nov 07, 2022
Andrey Ignatov, Grigory Malivenko, Radu Timofte, Lukasz Treszczotko, Xin Chang, Piotr Ksiazek, Michal Lopuszynski, Maciej Pioro, Rafal Rudnicki, Maciej Smyl, Yujie Ma, Zhenyu Li, Zehui Chen, Jialei Xu, Xianming Liu, Junjun Jiang, XueChao Shi, Difan Xu, Yanan Li, Xiaotao Wang, Lei Lei, Ziyu Zhang, Yicheng Wang, Zilong Huang, Guozhong Luo, Gang Yu, Bin Fu, Jiaqi Li, Yiran Wang, Zihao Huang, Zhiguo Cao, Marcos V. Conde, Denis Sapozhnikov, Byeong Hyun Lee, Dongwon Park, Seongmin Hong, Joonhee Lee, Seunggyu Lee, Se Young Chun

Figure 1 for Efficient Single-Image Depth Estimation on Mobile Devices, Mobile AI & AIM 2022 Challenge: Report

Figure 2 for Efficient Single-Image Depth Estimation on Mobile Devices, Mobile AI & AIM 2022 Challenge: Report

Figure 3 for Efficient Single-Image Depth Estimation on Mobile Devices, Mobile AI & AIM 2022 Challenge: Report

Figure 4 for Efficient Single-Image Depth Estimation on Mobile Devices, Mobile AI & AIM 2022 Challenge: Report

* arXiv admin note: substantial text overlap with arXiv:2105.08630, arXiv:2211.03885; text overlap with arXiv:2105.08819, arXiv:2105.08826, arXiv:2105.08629, arXiv:2105.07809, arXiv:2105.07825

Access Paper or Ask Questions

Adaptive GLCM sampling for transformer-based COVID-19 detection on CT

Jul 04, 2022
Okchul Jung, Dong Un Kang, Gwanghyun Kim, Se Young Chun

Figure 1 for Adaptive GLCM sampling for transformer-based COVID-19 detection on CT

Figure 2 for Adaptive GLCM sampling for transformer-based COVID-19 detection on CT

* 6 pages

Access Paper or Ask Questions

Self-supervised regression learning using domain knowledge: Applications to improving self-supervised denoising in imaging

May 10, 2022
Il Yong Chun, Dongwon Park, Xuehang Zheng, Se Young Chun, Yong Long

Figure 1 for Self-supervised regression learning using domain knowledge: Applications to improving self-supervised denoising in imaging

Figure 2 for Self-supervised regression learning using domain knowledge: Applications to improving self-supervised denoising in imaging

Figure 3 for Self-supervised regression learning using domain knowledge: Applications to improving self-supervised denoising in imaging

Figure 4 for Self-supervised regression learning using domain knowledge: Applications to improving self-supervised denoising in imaging

* 17 pages, 16 figures, 2 tables, submitted to IEEE T-IP

Access Paper or Ask Questions

Rethinking Deep Image Prior for Denoising

Aug 29, 2021
Yeonsik Jo, Se Young Chun, Jonghyun Choi

Figure 1 for Rethinking Deep Image Prior for Denoising

Figure 2 for Rethinking Deep Image Prior for Denoising

Figure 3 for Rethinking Deep Image Prior for Denoising

Figure 4 for Rethinking Deep Image Prior for Denoising

* ICCV 2021

Access Paper or Ask Questions

Blur More To Deblur Better: Multi-Blur2Deblur For Efficient Video Deblurring

Dec 23, 2020
Dongwon Park, Dong Un Kang, Se Young Chun

Figure 1 for Blur More To Deblur Better: Multi-Blur2Deblur For Efficient Video Deblurring

Figure 2 for Blur More To Deblur Better: Multi-Blur2Deblur For Efficient Video Deblurring

Figure 3 for Blur More To Deblur Better: Multi-Blur2Deblur For Efficient Video Deblurring

Figure 4 for Blur More To Deblur Better: Multi-Blur2Deblur For Efficient Video Deblurring

* 9 pages, 7 figures

Access Paper or Ask Questions