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AIM 2020 Challenge on Real Image Super-Resolution: Methods and Results [article]

Pengxu Wei, Hannan Lu, Radu Timofte, Liang Lin, Wangmeng Zuo, Zhihong Pan, Baopu Li, Teng Xi, Yanwen Fan, Gang Zhang, Jingtuo Liu, Junyu Han (+64 others)
<span title="2020-09-25">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
This paper introduces the real image Super-Resolution (SR) challenge that was part of the Advances in Image Manipulation (AIM) workshop, held in conjunction with ECCV 2020.  ...  The goal is to attract more attention to realistic image degradation for the SR task, which is much more complicated and challenging, and contributes to real-world image super-resolution applications.  ...  AIM 2020 Challenge on Real Image Super-Resolution The objectives of the AIM 2020 challenge on real image super-resolution challenge are: (i) to further explore the researches on real image SR; (ii) to  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2009.12072v1">arXiv:2009.12072v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/7cwsjfhqa5cf7avfvdabpmxrda">fatcat:7cwsjfhqa5cf7avfvdabpmxrda</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200929075953/https://arxiv.org/pdf/2009.12072v1.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/01/5f/015f35d1214cab344cc8c001db7313f1400e4504.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2009.12072v1" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

AIM 2019 Challenge on Video Temporal Super-Resolution: Methods and Results [article]

Seungjun Nah, Sanghyun Son, Radu Timofte, Kyoung Mu Lee
<span title="2020-05-04">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
This paper reviews the first AIM challenge on video temporal super-resolution (frame interpolation) with a focus on the proposed solutions and results.  ...  The challenge winning methods achieve the state-of-the-art in video temporal superresolution.  ...  Acknowledgments We thank the AIM 2019 sponsors. A. Teams and affiliations AIM 2019 team Title: AIM 2019 Challenge on Video Temporal Super-  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2005.01233v1">arXiv:2005.01233v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/aqxpmzat7jcwdiztapx5sttceq">fatcat:aqxpmzat7jcwdiztapx5sttceq</a> </span>
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AIM 2020 Challenge on Efficient Super-Resolution: Methods and Results [article]

Kai Zhang, Martin Danelljan, Yawei Li, Radu Timofte, Jie Liu, Jie Tang, Gangshan Wu, Yu Zhu, Xiangyu He, Wenjie Xu, Chenghua Li, Cong Leng (+73 others)
<span title="2020-09-15">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
This paper reviews the AIM 2020 challenge on efficient single image super-resolution with focus on the proposed solutions and results.  ...  The track had 150 registered participants, and 25 teams submitted the final results. They gauge the state-of-the-art in efficient single image super-resolution.  ...  Acknowledgements We thank the AIM 2020 sponsors: HUAWEI, MediaTek, Google, NVIDIA, Qualcomm, and Computer Vision Lab (CVL) ETH Zurich. A Teams and affiliations  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2009.06943v1">arXiv:2009.06943v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/2s7k5wsgsjgo5flnqaby26cn64">fatcat:2s7k5wsgsjgo5flnqaby26cn64</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200929192316/https://arxiv.org/pdf/2009.06943v1.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2009.06943v1" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

NTIRE 2020 Challenge on Real-World Image Super-Resolution: Methods and Results [article]

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 (+34 others)
<span title="2020-05-05">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
This paper reviews the NTIRE 2020 challenge on real world super-resolution. It focuses on the participating methods and final results.  ...  This is the second challenge on the subject, following AIM 2019, targeting to advance the state-of-the-art in super-resolution. To measure the performance we use the benchmark protocol from AIM 2019.  ...  Acknowledgements We thank the NTIRE 2020 sponsors: Huawei, Oppo, Voyage81, MediaTek, DisneyResearch|Studios, and Computer Vision Lab (CVL) ETH Zurich.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2005.01996v1">arXiv:2005.01996v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ewngd7chdve3fbvwis32v64ruq">fatcat:ewngd7chdve3fbvwis32v64ruq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200528032059/https://arxiv.org/pdf/2005.01996v1.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2005.01996v1" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

NTIRE 2020 Challenge on Perceptual Extreme Super-Resolution: Methods and Results [article]

Kai Zhang, Shuhang Gu, Radu Timofte, Taizhang Shang, Qiuju Dai, Shengchen Zhu, Tong Yang, Yandong Guo, Younghyun Jo, Sejong Yang, Seon Joo Kim, Lin Zha (+51 others)
<span title="2020-05-03">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
This paper reviews the NTIRE 2020 challenge on perceptual extreme super-resolution with focus on proposed solutions and results.  ...  The track had 280 registered participants, and 19 teams submitted the final results. They gauge the state-of-the-art in single image super-resolution.  ...  Acknowledgements We thank the NTIRE 2020 sponsors: HUAWEI, OPPO, Voyage81, MediaTek, DisneyResearch|Studios, and Computer Vision Lab (CVL) ETH Zurich.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2005.01056v1">arXiv:2005.01056v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/6nwj5ilbgbgjnmd6oy435hjdhi">fatcat:6nwj5ilbgbgjnmd6oy435hjdhi</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200513082158/https://arxiv.org/pdf/2005.01056v1.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2005.01056v1" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

AIM 2020 Challenge on Video Extreme Super-Resolution: Methods and Results [article]

Dario Fuoli, Zhiwu Huang, Shuhang Gu, Radu Timofte, Arnau Raventos, Aryan Esfandiari, Salah Karout, Xuan Xu, Xin Li, Xin Xiong, Jinge Wang, Pablo Navarrete Michelini (+14 others)
<span title="2020-09-14">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
This paper reviews the video extreme super-resolution challenge associated with the AIM 2020 workshop at ECCV 2020.  ...  In contrast to single image super-resolution (SISR), VSR can benefit from additional information in the temporal domain.  ...  Acknowledgements We thank the AIM 2020 sponsors: Huawei, MediaTek, NVIDIA, Qualcomm, Google, and Computer Vision Lab (CVL), ETH Zurich.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2009.06290v1">arXiv:2009.06290v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/bbgfzmwupfgcnigwr2onun4zzm">fatcat:bbgfzmwupfgcnigwr2onun4zzm</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200920185737/https://arxiv.org/pdf/2009.06290v1.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2009.06290v1" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Suitability of Single Image Super-Resolution Models for Video Super-Resolution

<span title="2020-06-30">2020</span> <i title="Blue Eyes Intelligence Engineering and Sciences Engineering and Sciences Publication - BEIESP"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/h673cvfolnhl3mnbjxkhtxdtg4" style="color: black;">International Journal of Engineering and Advanced Technology</a> </i> &nbsp;
We further draw a conclusion on the suitability and extent to which these models may be used for video super resolution.  ...  Single image super resolution algorithms refer to those algorithms that can be applied on a single image to enhance its resolution.  ...  An enhanced deep super-resolution network (EDSR) exceeds the performance of current state of the art Super Resolution methods.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.35940/ijeat.e9575.069520">doi:10.35940/ijeat.e9575.069520</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/6fpmkgqvvrcpjgyslaivsvwlpu">fatcat:6fpmkgqvvrcpjgyslaivsvwlpu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200721062849/https://www.ijeat.org/wp-content/uploads/papers/v9i5/E9575069520.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/aa/32/aa32011bf54c1d13c2c9c6b78a04f013ec076a90.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.35940/ijeat.e9575.069520"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a>

AIM 2020 Challenge on Video Temporal Super-Resolution [article]

Sanghyun Son, Jaerin Lee, Seungjun Nah, Radu Timofte, Kyoung Mu Lee
<span title="2020-09-28">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
This paper reports the second AIM challenge on Video Temporal Super-Resolution (VTSR), a.k.a. frame interpolation, with a focus on the proposed solutions, results, and analysis.  ...  The winning team proposes the enhanced quadratic video interpolation method and achieves state-of-the-art on the VTSR task.  ...  Acknowledgments We thank all AIM 2020 sponsors: Huawei Technologies Co. Ltd., MediaTek Inc., NVIDIA Corp., Qualcomm Inc., Google, LLC and CVL, ETH Zürich.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2009.12987v1">arXiv:2009.12987v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/23cngd3i25bupb5lwszpzxthte">fatcat:23cngd3i25bupb5lwszpzxthte</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200930123506/https://arxiv.org/pdf/2009.12987v1.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2009.12987v1" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

NTIRE 2020 Challenge on Video Quality Mapping: Methods and Results [article]

Dario Fuoli, Zhiwu Huang, Martin Danelljan, Radu Timofte, Hua Wang, Longcun Jin, Dewei Su, Jing Liu, Jaehoon Lee, Michal Kudelski, Lukasz Bala, Dmitry Hrybov (+9 others)
<span title="2020-06-15">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
This paper reviews the NTIRE 2020 challenge on video quality mapping (VQM), which addresses the issues of quality mapping from source video domain to target video domain.  ...  The challenge includes both a supervised track (track 1) and a weakly-supervised track (track 2) for two benchmark datasets.  ...  Acknowledgements We thank the NTIRE 2020 sponsors: Huawei, Oppo, Voyage81, MediaTek, DisneyResearch|Studios, and Computer Vision Lab (CVL) ETH Zurich.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2005.02291v3">arXiv:2005.02291v3</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/z5zgwpnyrveothp337xeb7yfoy">fatcat:z5zgwpnyrveothp337xeb7yfoy</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200623202512/https://arxiv.org/pdf/2005.02291v3.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/85/9e/859ec09c9b565bb2a0696e05ae9c36ad5a475b01.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2005.02291v3" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Real Image Super Resolution Via Heterogeneous Model Ensemble using GP-NAS [article]

Zhihong Pan, Baopu Li, Teng Xi, Yanwen Fan, Gang Zhang, Jingtuo Liu, Junyu Han, Errui Ding
<span title="2021-01-22">2021</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
The proposed method won the first place in all three tracks of the AIM 2020 Real Image Super-Resolution Challenge.  ...  While these models perform well on benchmark dataset where low-resolution (LR) images are constructed from high-resolution (HR) references with known blur kernel, real image SR is more challenging when  ...  and model-ensemble for full-size images. • The proposed method was applied for the AIM 2020 Real Image Super-Resolution Challenge and won the first place in all three tracks (upscaling factors of ×2,  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2009.01371v2">arXiv:2009.01371v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/nwoeffzuzvhdhldltcwzpp2iwq">fatcat:nwoeffzuzvhdhldltcwzpp2iwq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210129061614/https://arxiv.org/pdf/2009.01371v2.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/b6/23/b6236825dd0e649eee61a81896686e3162b28461.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2009.01371v2" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Unpaired Image Super-Resolution using Pseudo-Supervision [article]

Shunta Maeda
<span title="2020-02-26">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
In most studies on learning-based image super-resolution (SR), the paired training dataset is created by downscaling high-resolution (HR) images with a predetermined operation (e.g., bicubic).  ...  However, these methods fail to super-resolve real-world low-resolution (LR) images, for which the degradation process is much more complicated and unknown.  ...  Acknowledgement I thank Tatsuya Nagata, Shunsuke Ono, Kazuki Sekine, Hiraku Shibuya and Yusuke Uchida for helpful comments on the manuscript.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2002.11397v1">arXiv:2002.11397v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/xqrg7vlrzzfhheanqwmnhzuwl4">fatcat:xqrg7vlrzzfhheanqwmnhzuwl4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200321182124/https://arxiv.org/pdf/2002.11397v1.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2002.11397v1" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Super Resolution for Root Imaging [article]

Jose F. Ruiz-Munoz, Jyothier K. Nimmagadda, Tyler G. Dowd, and James E. Baciak, Alina Zare
<span title="2020-05-05">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Thus, an effective super-resolution (SR) algorithm is desired for overcoming resolution limitations of sensors, reducing storage space requirements, and boosting the performance of later analysis, such  ...  Therefore, we conclude that the quality of the image enhancement depends on the application.  ...  The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2003.13537v2">arXiv:2003.13537v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/swlsjapl65dlhnmx244v26zuqu">fatcat:swlsjapl65dlhnmx244v26zuqu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200529030158/https://arxiv.org/ftp/arxiv/papers/2003/2003.13537.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/09/f3/09f3ccae73fdd2dace0f6a64e230e5d526beae3c.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2003.13537v2" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Deep Cyclic Generative Adversarial Residual Convolutional Networks for Real Image Super-Resolution [article]

Rao Muhammad Umer, Christian Micheloni
<span title="2020-09-07">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
In addition, our SR results on the AIM 2020 Real Image SR Challenge datasets demonstrate that the proposed SR approach achieves comparable results as the other state-of-art methods.  ...  Recent deep learning based single image super-resolution (SISR) methods mostly train their models in a clean data domain where the low-resolution (LR) and the high-resolution (HR) images come from noise-free  ...  with the other state-of-art methods on the AIM 2020 Real Image SR (track-3) test set at the ×4 super-resolution.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2009.03693v1">arXiv:2009.03693v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/w2uoghkqbncqfnvz7e7inzhgla">fatcat:w2uoghkqbncqfnvz7e7inzhgla</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200918125740/https://arxiv.org/pdf/2009.03693v1.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2009.03693v1" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Perceptual Image Super-Resolution with Progressive Adversarial Network [article]

Lone Wong, Deli Zhao, Shaohua Wan, Bo Zhang
<span title="2020-03-19">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Single Image Super-Resolution (SISR) aims to improve resolution of small-size low-quality image from a single one.  ...  To address this issue, we propose Progressive Adversarial Network (PAN) that is capable of coping with this difficulty for domain-specific image super-resolution.  ...  Fig. 4 : 4 Super-resolution result of our methods compared with existing methods. Super-resolution images (1024 × 1024). (b) FID accuracy. Fig. 5 : 5 8× SR comparison.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2003.03756v4">arXiv:2003.03756v4</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/dg32vyec5ndhrhmpin7kp4uhwi">fatcat:dg32vyec5ndhrhmpin7kp4uhwi</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200323000055/https://arxiv.org/pdf/2003.03756v4.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2003.03756v4" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

FAN: Frequency Aggregation Network for Real Image Super-resolution [article]

Yingxue Pang, Xin Li, Xin Jin, Yaojun Wu, Jianzhao Liu, Sen Liu, Zhibo Chen
<span title="2020-09-30">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
We conduct extensive experiments quantitatively and qualitatively to verify that our FAN performs well on the real image super-resolution task of AIM 2020 challenge.  ...  Single image super-resolution (SISR) aims to recover the high-resolution (HR) image from its low-resolution (LR) input image. With the development of deep learning, SISR has achieved great progress.  ...  .: Ntire 2020 challenge on real-world image super-resolution: Methods and results.  ... 
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