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Jaejun Yoo
This is just a disambiguation page, and is not intended to be the bibliography of an actual person. Any publication listed on this page has not been assigned to an actual author yet. If you know the true author of one of the publications listed below, you are welcome to contact us.
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2020 – today
- 2024
- [j11]Ida Bagus Krishna Yoga Utama, Ones Sanjerico Sitanggang
, Muhammad Rangga Aziz Nasution
, Md. Ibne Joha
, Jaejun Yoo, Yeong Min Jang
:
Enhancing Optical Camera Communication Performance for Collaborative Communication Using Positioning Information. IEEE Access 12: 11795-11809 (2024) - [j10]Namhyuk Ahn, Jaejun Yoo
, Kyung-Ah Sohn:
Data Augmentation for Low-Level Vision: CutBlur and Mixture-of-Augmentation. Int. J. Comput. Vis. 132(6): 2041-2059 (2024) - [j9]Jeongho Min
, Yejun Lee
, Dongyoung Kim
, Jaejun Yoo
:
Bridging the Domain Gap: A Simple Domain Matching Method for Reference-Based Image Super-Resolution in Remote Sensing. IEEE Geosci. Remote. Sens. Lett. 21: 1-5 (2024) - [c22]Pum Jun Kim, Seojun Kim, Jaejun Yoo:
STREAM: Spatio-TempoRal Evaluation and Analysis Metric for Video Generative Models. ICLR 2024 - [c21]Dongyeun Lee, Chaewon Kim, Sangjoon Yu, Jaejun Yoo, Gyeong-Moon Park:
RADIO: Reference-Agnostic Dubbing Video Synthesis. WACV 2024: 4156-4166 - [i29]Jeongho Min, Yejun Lee, Dongyoung Kim, Jaejun Yoo:
Bridging the Domain Gap: A Simple Domain Matching Method for Reference-based Image Super-Resolution in Remote Sensing. CoRR abs/2401.15944 (2024) - [i28]Kihong Kim, Haneol Lee, Jihye Park, Seyeon Kim, Kwanghee Lee, Seungryong Kim, Jaejun Yoo:
Hybrid Video Diffusion Models with 2D Triplane and 3D Wavelet Representation. CoRR abs/2402.13729 (2024) - [i27]Pum Jun Kim, Seojun Kim, Jaejun Yoo:
STREAM: Spatio-TempoRal Evaluation and Analysis Metric for Video Generative Models. CoRR abs/2403.09669 (2024) - [i26]Jaejung Seol, Seojun Kim, Jaejun Yoo:
PosterLlama: Bridging Design Ability of Langauge Model to Contents-Aware Layout Generation. CoRR abs/2404.00995 (2024) - [i25]Sangyeop Yeo, Yoojin Jang, Jaejun Yoo:
Nickel and Diming Your GAN: A Dual-Method Approach to Enhancing GAN Efficiency via Knowledge Distillation. CoRR abs/2405.11614 (2024) - 2023
- [c20]Sangyeop Yeo, Yoojin Jang, Jy-yong Sohn, Dongyoon Han, Jaejun Yoo:
Can We Find Strong Lottery Tickets in Generative Models? AAAI 2023: 3267-3275 - [c19]Dongyeun Lee, Jae Young Lee, Doyeon Kim, Jaehyun Choi, Jaejun Yoo, Junmo Kim:
Fix the Noise: Disentangling Source Feature for Controllable Domain Translation. CVPR 2023: 14224-14234 - [c18]Jihye Park, Sunwoo Kim, Soohyun Kim, Seokju Cho, Jaejun Yoo, Youngjung Uh, Seungryong Kim:
LANIT: Language-Driven Image-to-Image Translation for Unlabeled Data. CVPR 2023: 23401-23411 - [c17]Yejun Lee
, Eun-Kyeong Kim
, Jaejun Yoo
:
Towards Robust Contrail Detection by Mitigating Label Bias via a Probabilistic Deep Learning Model: A Preliminary Study. SIGSPATIAL/GIS 2023: 3:1-3:2 - [c16]Pum Jun Kim, Yoojin Jang, Jisu Kim, Jaejun Yoo:
TopP&R: Robust Support Estimation Approach for Evaluating Fidelity and Diversity in Generative Models. NeurIPS 2023 - [i24]Dongyeun Lee, Jae Young Lee, Doyeon Kim, Jaehyun Choi, Jaejun Yoo, Junmo Kim:
Fix the Noise: Disentangling Source Feature for Controllable Domain Translation. CoRR abs/2303.11545 (2023) - [i23]Simo Ryu, Seunghyun Seo, Jaejun Yoo:
Efficient Storage of Fine-Tuned Models via Low-Rank Approximation of Weight Residuals. CoRR abs/2305.18425 (2023) - [i22]Pum Jun Kim, Yoojin Jang, Jisu Kim, Jaejun Yoo:
TopP&R: Robust Support Estimation Approach for Evaluating Fidelity and Diversity in Generative Models. CoRR abs/2306.08013 (2023) - [i21]Dongyeun Lee, Chaewon Kim, Sangjoon Yu, Jaejun Yoo, Gyeong-Moon Park:
RADIO: Reference-Agnostic Dubbing Video Synthesis. CoRR abs/2309.01950 (2023) - 2022
- [c15]Youngjae Lim, Yang Koo Lee, Jaejun Yoo, Daesub Yoon:
An Open Source-based Digital Twin Broker Interface for Interaction between Real and Virtual Assets. ICTC 2022: 1657-1659 - [e2]Nandinee Fariah Haq
, Patricia Johnson
, Andreas Maier
, Chen Qin, Tobias Würfl
, Jaejun Yoo
:
Machine Learning for Medical Image Reconstruction - 5th International Workshop, MLMIR 2022, Held in Conjunction with MICCAI 2022, Singapore, September 22, 2022, Proceedings. Lecture Notes in Computer Science 13587, Springer 2022, ISBN 978-3-031-17246-5 [contents] - [i20]Jihye Park, Soohyun Kim, Sunwoo Kim, Jaejun Yoo, Youngjung Uh
, Seungryong Kim:
LANIT: Language-Driven Image-to-Image Translation for Unlabeled Data. CoRR abs/2208.14889 (2022) - [i19]Sangyeop Yeo, Yoojin Jang, Jy-yong Sohn, Dongyoon Han, Jaejun Yoo:
Can We Find Strong Lottery Tickets in Generative Models? CoRR abs/2212.08311 (2022) - 2021
- [j8]Jaejun Yoo
, Kyong Hwan Jin
, Harshit Gupta
, Jérôme Yerly
, Matthias Stuber, Michael Unser
:
Time-Dependent Deep Image Prior for Dynamic MRI. IEEE Trans. Medical Imaging 40(12): 3337-3348 (2021) - [c14]Kyungjune Baek, Yunjey Choi, Youngjung Uh
, Jaejun Yoo, Hyunjung Shim:
Rethinking the Truly Unsupervised Image-to-Image Translation. ICCV 2021: 14134-14143 - [e1]Nandinee Fariah Haq
, Patricia Johnson
, Andreas Maier
, Tobias Würfl
, Jaejun Yoo
:
Machine Learning for Medical Image Reconstruction - 4th International Workshop, MLMIR 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, October 1, 2021, Proceedings. Lecture Notes in Computer Science 12964, Springer 2021, ISBN 978-3-030-88551-9 [contents] - 2020
- [j7]Jae Jun Yoo
, Sohail Sabir, Duchang Heo, Kee Hyun Kim, Abdul Wahab
, Yoonseok Choi, Seul-I Lee, Eun Young Chae, Hak Hee Kim, Young Min Bae, Young-Wook Choi, Seungryong Cho, Jong Chul Ye
:
Deep Learning Diffuse Optical Tomography. IEEE Trans. Medical Imaging 39(4): 877-887 (2020) - [c13]Namhyuk Ahn, Jaejun Yoo
, Kyung-Ah Sohn:
SimUSR: A Simple but Strong Baseline for Unsupervised Image Super-resolution. CVPR Workshops 2020: 1953-1961 - [c12]Andreas Lugmayr, Martin Danelljan, Radu Timofte
, Namhyuk Ahn, Dongwoon Bai, Jie Cai, Yun Cao, Junyang Chen, Kaihua Cheng, Se Young 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, Yonghyeok Seo, Wan-Chi Siu, Kyung-Ah Sohn, Ying Tai
, Rao Muhammad Umer, Shuangquan Wang, Huibing Wang, Timothy Haoning Wu, Haoning Wu, Biao Yang, Fuzhi Yang, Jaejun Yoo, Tongtong Zhao, Yuanbo Zhou, Haijie Zhuo, Ziyao Zong, Xueyi Zou:
NTIRE 2020 Challenge on Real-World Image Super-Resolution: Methods and Results. CVPR Workshops 2020: 2058-2076 - [c11]Yunjey Choi, Youngjung Uh
, Jaejun Yoo
, Jung-Woo Ha
:
StarGAN v2: Diverse Image Synthesis for Multiple Domains. CVPR 2020: 8185-8194 - [c10]Jaejun Yoo
, Namhyuk Ahn, Kyung-Ah Sohn:
Rethinking Data Augmentation for Image Super-resolution: A Comprehensive Analysis and a New Strategy. CVPR 2020: 8372-8381 - [c9]Harshit Gupta
, Thong H. Phan
, Jaejun Yoo
, Michael Unser
:
Multi-CryoGAN: Reconstruction of Continuous Conformations in Cryo-EM Using Generative Adversarial Networks. ECCV Workshops (1) 2020: 429-444 - [c8]Muhammad Ferjad Naeem, Seong Joon Oh, Youngjung Uh, Yunjey Choi, Jaejun Yoo:
Reliable Fidelity and Diversity Metrics for Generative Models. ICML 2020: 7176-7185 - [i18]Muhammad Ferjad Naeem, Seong Joon Oh, Youngjung Uh, Yunjey Choi, Jaejun Yoo:
Reliable Fidelity and Diversity Metrics for Generative Models. CoRR abs/2002.09797 (2020) - [i17]Jaejun Yoo, Namhyuk Ahn, Kyung-Ah Sohn:
Rethinking Data Augmentation for Image Super-resolution: A Comprehensive Analysis and a New Strategy. CoRR abs/2004.00448 (2020) - [i16]Namhyuk Ahn, Jaejun Yoo, Kyung-Ah Sohn:
SimUSR: A Simple but Strong Baseline for Unsupervised Image Super-resolution. CoRR abs/2004.11020 (2020) - [i15]Andreas Lugmayr, Martin Danelljan, Radu Timofte, Namhyuk Ahn, Dongwoon Bai, Jie Cai, Yun Cao, Junyang Chen, Kaihua Cheng, Se Young 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, Yonghyeok Seo, Wan-Chi Siu, Kyung-Ah Sohn, Ying Tai, Rao Muhammad Umer, Shuangquan Wang, Huibing Wang, Timothy Haoning Wu, Haoning Wu, Biao Yang, Fuzhi Yang, Jaejun Yoo, Tongtong Zhao, Yuanbo Zhou, Haijie Zhuo, Ziyao Zong, Xueyi Zou:
NTIRE 2020 Challenge on Real-World Image Super-Resolution: Methods and Results. CoRR abs/2005.01996 (2020) - [i14]Kyungjune Baek, Yunjey Choi, Youngjung Uh, Jaejun Yoo, Hyunjung Shim:
Rethinking the Truly Unsupervised Image-to-Image Translation. CoRR abs/2006.06500 (2020)
2010 – 2019
- 2019
- [j6]Jae-Jun Yoo, Woong-Kee Loh
, Kyu-Young Whang:
Indexable sub-trajectory matching using multi-segment approximation: a partition-and-stitch framework. J. Supercomput. 75(9): 6129-6157 (2019) - [c7]Jaejun Yoo
, Youngjung Uh
, Sanghyuk Chun, Byeongkyu Kang, Jung-Woo Ha
:
Photorealistic Style Transfer via Wavelet Transforms. ICCV 2019: 9035-9044 - [c6]Sang-Woo Lee, Tong Gao, Sohee Yang, Jaejun Yoo, Jung-Woo Ha:
Large-Scale Answerer in Questioner's Mind for Visual Dialog Question Generation. ICLR (Poster) 2019 - [i13]Sang-Woo Lee, Tong Gao, Sohee Yang, Jaejun Yoo, Jung-Woo Ha:
Large-Scale Answerer in Questioner's Mind for Visual Dialog Question Generation. CoRR abs/1902.08355 (2019) - [i12]Jaejun Yoo, Youngjung Uh, Sanghyuk Chun, Byeongkyu Kang, Jung-Woo Ha:
Photorealistic Style Transfer via Wavelet Transforms. CoRR abs/1903.09760 (2019) - [i11]Young Joon Yoo, Sanghyuk Chun, Sangdoo Yun, Jung-Woo Ha, Jaejun Yoo:
Neural Approximation of an Auto-Regressive Process through Confidence Guided Sampling. CoRR abs/1910.06705 (2019) - [i10]Yunjey Choi, Youngjung Uh, Jaejun Yoo, Jung-Woo Ha:
StarGAN v2: Diverse Image Synthesis for Multiple Domains. CoRR abs/1912.01865 (2019) - 2018
- [j5]Jaejun Yoo, Ki-Hoon Lee, Young-Ho Jeon:
Migration from RDBMS to NoSQL Using Column-level Denormalization and Atomic Aggregates. J. Inf. Sci. Eng. 34(1): 243-259 (2018) - [j4]Jae Jun Yoo
, Abdul Wahab
, Jong Chul Ye:
A Mathematical Framework for Deep Learning in Elastic Source Imaging. SIAM J. Appl. Math. 78(5): 2791-2818 (2018) - [j3]Dongwook Lee
, Jae Jun Yoo
, Sungho Tak
, Jong Chul Ye
:
Deep Residual Learning for Accelerated MRI Using Magnitude and Phase Networks. IEEE Trans. Biomed. Eng. 65(9): 1985-1995 (2018) - [j2]Eunhee Kang, Won Chang
, Jae Jun Yoo
, Jong Chul Ye
:
Deep Convolutional Framelet Denosing for Low-Dose CT via Wavelet Residual Network. IEEE Trans. Medical Imaging 37(6): 1358-1369 (2018) - [i9]Jae Jun Yoo, Abdul Wahab, Jong Chul Ye:
A Mathematical Framework for Deep Learning in Elastic Source Imaging. CoRR abs/1802.10055 (2018) - [i8]Dongwook Lee, Jae Jun Yoo, Sungho Tak, Jong Chul Ye:
Deep Residual Learning for Accelerated MRI using Magnitude and Phase Networks. CoRR abs/1804.00432 (2018) - [i7]Jang-Hyun Kim, Jaejun Yoo, Sanghyuk Chun, Adrian Kim, Jung-Woo Ha:
Multi-Domain Processing via Hybrid Denoising Networks for Speech Enhancement. CoRR abs/1812.08914 (2018) - 2017
- [j1]Jae Jun Yoo
, Younghoon Jung
, Mikyoung Lim
, Jong Chul Ye, Abdul Wahab
:
A Joint Sparse Recovery Framework for Accurate Reconstruction of Inclusions in Elastic Media. SIAM J. Imaging Sci. 10(3): 1104-1138 (2017) - [c5]Radu Timofte
, Eirikur Agustsson, Luc Van Gool, Ming-Hsuan Yang, Lei Zhang, Bee Lim, Sanghyun Son, Heewon Kim, Seungjun Nah, Kyoung Mu Lee, Xintao Wang, Yapeng Tian, Ke Yu, Yulun Zhang, Shixiang Wu, Chao Dong, Liang Lin, Yu Qiao, Chen Change Loy, Woong Bae, Jae Jun Yoo
, Yoseob Han, Jong Chul Ye, Jae-Seok Choi, Munchurl Kim, Yuchen Fan, Jiahui Yu, Wei Han, Ding Liu
, Haichao Yu, Zhangyang Wang, Honghui Shi, Xinchao Wang, Thomas S. Huang, Yunjin Chen, Kai Zhang, Wangmeng Zuo, Zhimin Tang, Linkai Luo, Shaohui Li, Min Fu, Lei Cao, Wen Heng, Giang Bui, Truc Le, Ye Duan, Dacheng Tao, Ruxin Wang, Xu Lin, Jianxin Pang, Jinchang Xu, Yu Zhao, Xiangyu Xu, Jin-shan Pan, Deqing Sun, Yujin Zhang, Xibin Song, Yuchao Dai, Xueying Qin, Xuan-Phung Huynh, Tiantong Guo, Hojjat Seyed Mousavi, Tiep Huu Vu, Vishal Monga, Cristóvão Cruz, Karen O. Egiazarian, Vladimir Katkovnik, Rakesh Mehta, Arnav Kumar Jain, Abhinav Agarwalla, Ch V. Sai Praveen, Ruofan Zhou, Hongdiao Wen, Che Zhu, Zhiqiang Xia, Zhengtao Wang, Qi Guo:
NTIRE 2017 Challenge on Single Image Super-Resolution: Methods and Results. CVPR Workshops 2017: 1110-1121 - [c4]Woong Bae, Jae Jun Yoo
, Jong Chul Ye:
Beyond Deep Residual Learning for Image Restoration: Persistent Homology-Guided Manifold Simplification. CVPR Workshops 2017: 1141-1149 - [c3]Dongwook Lee
, Jae Jun Yoo
, Jong Chul Ye:
Deep residual learning for compressed sensing MRI. ISBI 2017: 15-18 - [i6]Dongwook Lee, Jae Jun Yoo, Jong Chul Ye:
Deep artifact learning for compressed sensing and parallel MRI. CoRR abs/1703.01120 (2017) - [i5]Yoseob Han, Jae Jun Yoo, Jong Chul Ye:
Deep Learning with Domain Adaptation for Accelerated Projection Reconstruction MR. CoRR abs/1703.01135 (2017) - [i4]Eunhee Kang, Jae Jun Yoo, Jong Chul Ye:
Wavelet Residual Network for Low-Dose CT via Deep Convolutional Framelets. CoRR abs/1707.09938 (2017) - [i3]Jae Jun Yoo, Sohail Sabir, Duchang Heo, Kee Hyun Kim, Abdul Wahab, Yoonseok Choi, Seul-I Lee, Eun Young Chae, Hak Hee Kim, Young Min Bae, Young-Wook Choi, Seungryong Cho, Jong Chul Ye:
Deep Learning Can Reverse Photon Migration for Diffuse Optical Tomography. CoRR abs/1712.00912 (2017) - 2016
- [i2]Woong Bae, Jae Jun Yoo, Jong Chul Ye:
Beyond Deep Residual Learning for Image Restoration: Persistent Homology-Guided Manifold Simplification. CoRR abs/1611.06345 (2016) - [i1]Yoseob Han, Jae Jun Yoo, Jong Chul Ye:
Deep Residual Learning for Compressed Sensing CT Reconstruction via Persistent Homology Analysis. CoRR abs/1611.06391 (2016) - 2013
- [c2]Jae Jun Yoo
, Jongmin Kim, Chang-Hwan Im, Jong Chul Ye:
Neuroelectromagnetic imaging of correlated sources using a novel subspace penalized sparse learning. ISBI 2013: 552-555
2000 – 2009
- 2007
- [c1]Kyungbok Sung, Jae Jun Yoo, Dohyun Kim:
Collision Warning System on a Curved Road Using Wireless Sensor Networks. VTC Fall 2007: 1942-1946
Coauthor Index
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