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NTIRE 2019 Challenge on Video Super-Resolution: Methods and Results
2019
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
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This paper reviews the first NTIRE challenge on video super-resolution (restoration of rich details in lowresolution video frames) with focus on proposed solutions and results. ...
A new REalistic and Diverse Scenes dataset (REDS) was employed. The challenge was divided into 2 tracks. ...
Acknowledgments We thank the NTIRE 2019 sponsors: OPPO Mobile Corp., Ltd., NVIDIA Corp., HUAWEI Technologies Co. Ltd., SAMSUNG Electronics Co., Ltd., Amazon.com, Inc., MediaTek Inc., and ETH Zurich. ...
doi:10.1109/cvprw.2019.00250
dblp:conf/cvpr/NahTGBHMSL19
fatcat:ki2tjqevi5fetinml3tynd7u3m
NTIRE 2020 Challenge on Image and Video Deblurring
[article]
2020
arXiv
pre-print
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Motion blur is one of the most common degradation artifacts in dynamic scene photography. This paper reviews the NTIRE 2020 Challenge on Image and Video Deblurring. ...
The winning methods demonstrate the state-ofthe-art performance on image and video deblurring tasks. ...
Acknowledgments We thank the NTIRE 2020 sponsors: HUAWEI Technologies Co. Ltd., OPPO Mobile Corp., Ltd., Voyage81, MediaTek Inc., DisneyResearch|Studios, and ETH Zurich (Computer Vision Lab). ...
arXiv:2005.01244v2
fatcat:aoy3tyxlybefrd7yd5ywvr6jh4
Deblurring via Stochastic Refinement
[article]
2021
arXiv
pre-print
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These results show clear benefits of our diffusion-based method for deblurring and challenge the widely used strategy of producing a single, deterministic reconstruction. ...
We present an alternative framework for blind deblurring based on conditional diffusion models. ...
These
results show clear benefits of our diffusion-based method
for deblurring and challenge the widely used strategy of ...
arXiv:2112.02475v2
fatcat:hi5fbbjuijhwnlq624bhrqfkiu
FMD-cGAN: Fast Motion Deblurring using Conditional Generative Adversarial Networks
[article]
2021
arXiv
pre-print
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The resulting compressed Deblurring cGAN faster than its closest competitors and even qualitative and quantitative results outperform various recently proposed state-of-the-art blind motion deblurring ...
We can also use our model for real-time image deblurring tasks. The current experiment on the standard datasets shows the effectiveness of the proposed method. ...
S.Nah,S.Baik,S.Hong,G.Moon,S.Son,R.Timofte,K.M.Lee: NTIRE 2019 Challenge on Video Deblurring and Super-
Resolution: Dataset and Study. CVPR Workshops, June, 2019
40. ...
arXiv:2111.15438v2
fatcat:ouphc37dp5avnhxrrvgx47dbge
NTIRE 2020 Challenge on Perceptual Extreme Super-Resolution: Methods and Results
[article]
2020
arXiv
pre-print
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This paper reviews the NTIRE 2020 challenge on perceptual extreme super-resolution with focus on proposed solutions and results. ...
The challenge task was to super-resolve an input image with a magnification factor 16 based on a set of prior examples of low and corresponding high resolution images. ...
Acknowledgements We thank the NTIRE 2020 sponsors: HUAWEI, OPPO, Voyage81, MediaTek, DisneyResearch|Studios, and Computer Vision Lab (CVL) ETH Zurich. ...
arXiv:2005.01056v1
fatcat:6nwj5ilbgbgjnmd6oy435hjdhi
NTIRE 2020 Challenge on Real Image Denoising: Dataset, Methods and Results
[article]
2020
arXiv
pre-print
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This paper reviews the NTIRE 2020 challenge on real image denoising with focus on the newly introduced dataset, the proposed methods and their results. ...
The challenge is a new version of the previous NTIRE 2019 challenge on real image denoising that was based on the SIDD benchmark. ...
Acknowledgements We thank the NTIRE 2020 sponsors: Huawei, Oppo, Voyage81, MediaTek, DisneyResearch|Studios, and Computer Vision Lab (CVL) ETH Zurich.
A. Teams and ...
arXiv:2005.04117v1
fatcat:iwtpyxikerbqhhvkpmwghqxeke
NTIRE 2020 Challenge on Real-World Image Super-Resolution: Methods and Results
[article]
2020
arXiv
pre-print
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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. ...
arXiv:2005.01996v1
fatcat:ewngd7chdve3fbvwis32v64ruq
EDVR: Video Restoration with Enhanced Deformable Convolutional Networks
[article]
2019
arXiv
pre-print
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EDVR also demonstrates superior performance to state-of-the-art published methods on video super-resolution and deblurring. The code is available at https://github.com/xinntao/EDVR. ...
This new benchmark challenges existing methods from two aspects: (1) how to align multiple frames given large motions, and (2) how to effectively fuse different frames with diverse motion and blur. ...
This work is supported by SenseTime Group Limited, Joint Lab of CAS-HK, the General Research Fund sponsored by the Research Grants Council of the Hong Kong SAR (CUHK 14241716, 14224316. 14209217), and ...
arXiv:1905.02716v1
fatcat:6bl4zdhvxfhldmfc76ie4gbkoe
Gated Fusion Network for Degraded Image Super Resolution
[article]
2020
arXiv
pre-print
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Experiments on these scenarios demonstrate that the proposed method performs more efficiently and favorably against the state-of-the-art approaches on benchmark datasets. ...
the final high-resolution prediction results. ...
In: IEEE International Conference on Computer Vision 3 B List of the Evaluated Methods Agustsson E, Timofte R (2017) Ntire 2017 challenge on
single image super-resolution: Dataset and study. ...
arXiv:2003.00893v2
fatcat:wslyimhivzh6pphadcmuxuuzsm
NTIRE 2020 Challenge on NonHomogeneous Dehazing
[article]
2020
arXiv
pre-print
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This paper reviews the NTIRE 2020 Challenge on NonHomogeneous Dehazing of images (restoration of rich details in hazy image). ...
We focus on the proposed solutions and their results evaluated on NH-Haze, a novel dataset consisting of 55 pairs of real haze free and nonhomogeneous hazy images recorded outdoor. ...
This challenge is one of the NTIRE 2020 associated challenges on: deblurring [44] , nonhomogeneous dehazing [12] , perceptual extreme super-resolution [67] , video quality mapping [21] , real image ...
arXiv:2005.03457v1
fatcat:3j6klhwog5bi3powihxdlrjgeq
Understanding Deformable Alignment in Video Super-Resolution
[article]
2020
arXiv
pre-print
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video super-resolution. ...
Based on our observations, we propose an offset-fidelity loss that guides the offset learning with optical flow. ...
.; and
Dong, C.; Loy, C. C.; He, K.; and Tang, X. 2014. Learning a Deep Mu Lee, K. 2019a. NTIRE 2019 Challenge on Video Deblurring
Convolutional Network for Image Super-resolution. ...
arXiv:2009.07265v1
fatcat:pwxa6xza75fqzp34czzg5fqu3q
Video Super Resolution Based on Deep Learning: A Comprehensive Survey
[article]
2022
arXiv
pre-print
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In this survey, we comprehensively investigate 33 state-of-the-art video super-resolution (VSR) methods based on deep learning. ...
Finally, we summarize and compare the performance of the representative VSR method on some benchmark datasets. ...
Zekun Li (Master student at School of Artificial Intelligence in Xidian University) and Dr. ...
arXiv:2007.12928v3
fatcat:nxoejcfdnzas3jznbqsale36ty
Fast Deep Multi-patch Hierarchical Network for Nonhomogeneous Image Dehazing
[article]
2020
arXiv
pre-print
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Our proposed method is quite robust for different environments with various density of the haze or fog in the scene and very lightweight as the total size of the model is around 21.7 MB. ...
Finally, we show the superiority of this network on Dense Haze Removal to other state-of-the-art models. ...
Figure 5: Qualitative results on NH-HAZE [3] Validation dataset.Table 1: Quantitative results on NH-HAZE[3] Validation set.We participated in NTIRE 2020 challenge on NonHomogeneous Image Dehazing [5] ...
arXiv:2005.05999v1
fatcat:jsamgnc5rrel3nkxmjhtet7kwa
Artificial Intelligence in the Creative Industries: A Review
[article]
2021
arXiv
pre-print
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The potential of AI (or its developers) to win awards for its original creations in competition with human creatives is also limited, based on contemporary technologies. ...
information extraction and enhancement, and v) data compression. ...
NTIRE 2020 held a denoising grand challenge within the IEEE CVPR conference that compared many contemporary high performing ML denoising methods on real images (Abdelhamed et al., 2020) . ...
arXiv:2007.12391v5
fatcat:mn2xqeylyrbabbu5zwln3admtm
Artificial intelligence in the creative industries: a review
2021
Artificial Intelligence Review
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The potential of AI (or its developers) to win awards for its original creations in competition with human creatives is also limited, based on contemporary technologies. ...
(iv) information extraction and enhancement, and (v) data compression. ...
NTIRE 2020 held a denoising grand challenge within the IEEE CVPR conference that compared many contemporary high performing ML denoising methods on real images (Abdelhamed et al. 2020) . ...
doi:10.1007/s10462-021-10039-7
fatcat:tcctdi7vprfx7mlujvqmpiy3ru
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