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- Yoo, Jaejun
- Lab. of Advanced Imaging Technology
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| DC Field | Value | Language |
|---|---|---|
| dc.citation.conferencePlace | US | - |
| dc.citation.conferencePlace | Honolulu, HI, USA | - |
| dc.citation.endPage | 1121 | - |
| dc.citation.startPage | 1110 | - |
| dc.citation.title | IEEE Conference on Computer Vision and Pattern Recognition | - |
| dc.contributor.author | Timofte, R. | - |
| dc.contributor.author | Agustsson, E. | - |
| dc.contributor.author | Gool, L.V. | - |
| dc.contributor.author | Yang, M.-H. | - |
| dc.contributor.author | Zhang, L. | - |
| dc.contributor.author | Lim, B. | - |
| dc.contributor.author | Son, S. | - |
| dc.contributor.author | Kim, H. | - |
| dc.contributor.author | Nah, S. | - |
| dc.contributor.author | Lee, K.M. | - |
| dc.contributor.author | Wang, X. | - |
| dc.contributor.author | Tian, Y. | - |
| dc.contributor.author | Yu, K. | - |
| dc.contributor.author | Zhang, Y. | - |
| dc.contributor.author | Wu, S. | - |
| dc.contributor.author | Dong, C. | - |
| dc.contributor.author | Lin, L. | - |
| dc.contributor.author | Qiao, Y. | - |
| dc.contributor.author | Loy, C.C. | - |
| dc.contributor.author | Bae, W. | - |
| dc.contributor.author | Yoo, Jaejun | - |
| dc.contributor.author | Han, Y. | - |
| dc.contributor.author | Ye, J.C. | - |
| dc.contributor.author | Choi, J.-S. | - |
| dc.contributor.author | Kim, M. | - |
| dc.contributor.author | Fan, Y. | - |
| dc.contributor.author | Yu, J. | - |
| dc.contributor.author | Han, W. | - |
| dc.contributor.author | Liu, D. | - |
| dc.contributor.author | Yu, H. | - |
| dc.contributor.author | Wang, Z. | - |
| dc.contributor.author | Shi, H. | - |
| dc.contributor.author | Huang, T.S. | - |
| dc.contributor.author | Chen, Y. | - |
| dc.contributor.author | Zhang, K. | - |
| dc.contributor.author | Zuo, W. | - |
| dc.contributor.author | Tang, Z. | - |
| dc.contributor.author | Luo, L. | - |
| dc.contributor.author | Li, S. | - |
| dc.contributor.author | Fu, M. | - |
| dc.contributor.author | Cao, L. | - |
| dc.contributor.author | Heng, W. | - |
| dc.contributor.author | Bui, G. | - |
| dc.contributor.author | Le, T. | - |
| dc.contributor.author | Duan, Y. | - |
| dc.contributor.author | Tao, D. | - |
| dc.contributor.author | Wang, R. | - |
| dc.contributor.author | Lin, X. | - |
| dc.contributor.author | Pang, J. | - |
| dc.contributor.author | Xu, J. | - |
| dc.contributor.author | Zhao, Y. | - |
| dc.contributor.author | Xu, X. | - |
| dc.contributor.author | Pan, J. | - |
| dc.contributor.author | Sun, D. | - |
| dc.contributor.author | Song, X. | - |
| dc.contributor.author | Dai, Y. | - |
| dc.contributor.author | Qin, X. | - |
| dc.contributor.author | Huynh, X.-P. | - |
| dc.contributor.author | Guo, T. | - |
| dc.contributor.author | Mousavi, H.S. | - |
| dc.contributor.author | Vu, T.H. | - |
| dc.contributor.author | Monga, V. | - |
| dc.contributor.author | Cruz, C. | - |
| dc.contributor.author | Egiazarian, K. | - |
| dc.contributor.author | Katkovnik, V. | - |
| dc.contributor.author | Mehta, R. | - |
| dc.contributor.author | Jain, A.K. | - |
| dc.contributor.author | Agarwalla, A. | - |
| dc.contributor.author | Praveen, C.V.S. | - |
| dc.contributor.author | Zhou, R. | - |
| dc.contributor.author | Wen, H. | - |
| dc.contributor.author | Zhu, C. | - |
| dc.contributor.author | Xia, Z. | - |
| dc.contributor.author | Guo, Q. | - |
| dc.date.accessioned | 2023-12-19T18:38:47Z | - |
| dc.date.available | 2023-12-19T18:38:47Z | - |
| dc.date.created | 2021-08-19 | - |
| dc.date.issued | 2017-07 | - |
| dc.description.abstract | This paper reviews the first challenge on single image super-resolution (restoration of rich details in an low resolution image) with focus on proposed solutions and results. A new DIVerse 2K resolution image dataset (DIV2K) was employed. The challenge had 6 competitions divided into 2 tracks with 3 magnification factors each. Track 1 employed the standard bicubic downscaling setup, while Track 2 had unknown downscaling operators (blur kernel and decimation) but learnable through low and high res train images. Each competition had b∼100 registered participants and 20 teams competed in the final testing phase. They gauge the state-of-the-art in single image super-resolution. | - |
| dc.identifier.bibliographicCitation | IEEE Conference on Computer Vision and Pattern Recognition, pp.1110 - 1121 | - |
| dc.identifier.doi | 10.1109/CVPRW.2017.149 | - |
| dc.identifier.issn | 2160-7508 | - |
| dc.identifier.scopusid | 2-s2.0-85030220122 | - |
| dc.identifier.uri | https://scholarworks.unist.ac.kr/handle/201301/53622 | - |
| dc.identifier.url | https://ieeexplore.ieee.org/document/8014883 | - |
| dc.language | 영어 | - |
| dc.publisher | IEEE Computer Society | - |
| dc.title | NTIRE 2017 Challenge on Single Image Super-Resolution: Methods and Results | - |
| dc.type | Conference Paper | - |
| dc.date.conferenceDate | 2017-07-21 | - |
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