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NTIRE 2019 Challenge on Video Super-Resolution: Methods and Results

Seungjun Nah, Radu Timofte, Shuhang Gu, Sungyong Baik, Seokil Hong, Gyeongsik Moon, Sanghyun Son, Kyoung Mu Lee, Xintao Wang, Kelvin C.K. Chan, Ke Yu, Chao Dong (+48 others)
2019 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)  
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]

Seungjun Nah, Sanghyun Son, Radu Timofte, Kyoung Mu Lee
2020 arXiv   pre-print
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]

Jay Whang, Mauricio Delbracio, Hossein Talebi, Chitwan Saharia, Alexandros G. Dimakis, Peyman Milanfar
2021 arXiv   pre-print
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]

Jatin Kumar and Indra Deep Mastan and Shanmuganathan Raman
2021 arXiv   pre-print
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]

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)
2020 arXiv   pre-print
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]

Abdelrahman Abdelhamed, Mahmoud Afifi, Radu Timofte, Michael S. Brown, Yue Cao, Zhilu Zhang, Wangmeng Zuo, Xiaoling Zhang, Jiye Liu, Wendong Chen, Changyuan Wen, Meng Liu (+78 others)
2020 arXiv   pre-print
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]

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)
2020 arXiv   pre-print
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]

Xintao Wang, Kelvin C.K. Chan, Ke Yu, Chao Dong, Chen Change Loy
2019 arXiv   pre-print
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]

Xinyi Zhang, Hang Dong, Zhe Hu, Wei-Sheng Lai, Fei Wang, Ming-Hsuan Yang
2020 arXiv   pre-print
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]

Codruta O. Ancuti, Cosmin Ancuti, Florin-Alexandru Vasluianu, Radu Timofte, Jing Liu, Haiyan Wu, Yuan Xie, Yanyun Qu, Lizhuang Ma, Ziling Huang, Qili Deng, Ju-Chin Chao (+40 others)
2020 arXiv   pre-print
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]

Kelvin C.K. Chan, Xintao Wang, Ke Yu, Chao Dong, Chen Change Loy
2020 arXiv   pre-print
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]

Hongying Liu, Zhubo Ruan, Peng Zhao, Chao Dong, Fanhua Shang, Yuanyuan Liu, Linlin Yang, Radu Timofte
2022 arXiv   pre-print
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]

Sourya Dipta Das, Saikat Dutta
2020 arXiv   pre-print
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]

Nantheera Anantrasirichai, David Bull
2021 arXiv   pre-print
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

Nantheera Anantrasirichai, David Bull
2021 Artificial Intelligence Review  
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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