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NTIRE 2019 : CVPR 2019- New Trends in Image Restoration and Enhancement workshop and challenges


When Jun 17, 2019 - Jun 17, 2019
Where Long Beach, California
Submission Deadline Mar 18, 2019
Notification Due Apr 5, 2019
Final Version Due Apr 16, 2019
Categories    image processing   deep learning   generative models   computer graphics

Call For Papers

NTIRE: 4th New Trends in Image Restoration and Enhancement workshop and challenges 2019
In conjunction with CVPR 2019

Contact: radu.timofte [at]


Image restoration and image enhancement are key computer vision tasks, aiming at the restoration of degraded image content, the filling in of missing information, or the needed transformation and/or manipulation to achieve a desired target (with respect to perceptual quality, contents, or performance of apps working on such images). Recent years have witnessed an increased interest from the vision and graphics communities in these fundamental topics of research. Not only has there been a constantly growing flow of related papers, but also substantial progress has been achieved.

Each step forward eases the use of images by people or computers for the fulfillment of further tasks, as image restoration or enhancement serves as an important frontend. Not surprisingly then, there is an ever growing range of applications in fields such as surveillance, the automotive industry, electronics, remote sensing, or medical image analysis etc. The emergence and ubiquitous use of mobile and wearable devices offer another fertile ground for additional applications and faster methods.

This workshop aims to provide an overview of the new trends and advances in those areas. Moreover, it will offer an opportunity for academic and industrial attendees to interact and explore collaborations.

This workshop builds upon the success of the previous NTIRE editions: at CVPR 2017 and 2018 and at ACCV 2016 . Moreover, it relies on all the people associated with the NTIRE past events such as organizers, PC members, distinguished speakers, authors of published paper, challenge participants and winning teams.


Papers addressing topics related to image/video restoration and enhancement are invited. The topics include, but are not limited to:

● Image/video inpainting
● Image/video deblurring
● Image/video denoising
● Image/video upsampling and super-resolution
● Image/video filtering
● Image/video dehazing
● Demosaicing
● Image/video compression
● Artifact removal
● Image/video enhancement: brightening, color adjustment, sharpening, etc.
● Style transfer
● Image/video generation and hallucination
● Image/video quality assessment
● Hyperspectral imaging
● Underwater imaging
● Aerial and satellite imaging
● Methods robust to changing weather conditions / adverse outdoor conditions
● Perceptual enhancement
● Studies and applications of the above.


A paper submission has to be in English, in pdf format, and at most 8 pages (excluding references) in CVPR style. The paper format must follow the same guidelines as for all CVPR submissions.
The review process is double blind. Authors do not know the names of the chair/reviewers of their papers. Reviewers do not know the names of the authors.
Dual submission is allowed with CVPR main conference only. If a paper is submitted also to CVPR and accepted, the paper cannot be published both at the CVPR and the workshop.

For the paper submissions, please go to the online submission site

Accepted and presented papers will be published after the conference in the CVPR Workshops Proceedings on by IEEE ( and Computer Vision Foundation (

The author kit provides a LaTeX2e template for paper submissions. Please refer to the example for detailed formatting instructions. If you use a different document processing system then see the CVPR author instruction page.

Author Kit:

Workshop Dates

● Submission Deadline: March 18, 2019 (EXTENDED)
● Decisions: April 5, 2018
● Camera Ready Deadline: April 16, 2019

NTIRE 2019 has the following associated groups of challenges (ONGOING!):

● image restoration and enhancement challenges:
● image dehazing (real hazy and haze-free images)
● image denoising (real noisy and noise-free images)
● image super-resolution (real low and high res images)
● image enhancement (real low and high quality images)
● image colorization
● video restoration and enhancement challenges:
● video deblurring (realistic blur, novel dataset)
● video super-resolution (realistic downsampling, novel dataset)


To learn more about the challenges and to participate:

Challenges Dates

● Release of train data: January 10, 2019
● Validation server online: January 15, 2019
● Competitions end: March 26, 2019


● Radu Timofte, ETH Zurich, Switzerland
● Shuhang Gu, ETH Zurich, Switzerland
● Lei Zhang, The Hong Kong Polytechnic University
● Ming-Hsuan Yang, University of California at Merced, US
● Luc Van Gool, KU Leuven, Belgium and ETH Zurich, Switzerland
● Cosmin Ancuti, Université catholique de Louvain (UCL), Belgium
● Codruta O. Ancuti, University Politehnica Timisoara, Romania
● Kyoung Mu Lee, Seoul National University, Korea
● Michael S. Brown, York University, Canada
● Eli Shechtman, Adobe Research
● Ming-Yu Liu, Nvidia
● Zhiwu Huang, ETH Zurich, Switzerland
● Seungjun Nah, Seoul National University, Korea
● Jianrui Cai, The Hong Kong Polytechnic University
● Richard Zhang, Adobe Research
● Andrey Ignatov, ETH Zurich, Switzerland
● Abdelrahman Kamel Siddek Abdelhamed, York University, Canada

Program Committee (to be updated)

Cosmin Ancuti, Universitatea Politehnica Timisoara, Romania
Nick Barnes, Data61, Australia
Michael S. Brown, York University, Canada
Subhasis Chaudhuri, IIT Bombay, India
Sunghyun Cho, Samsung
Christophe De Vleeschouwer, Université catholique de Louvain (UCL), Belgium
Chao Dong, SenseTime
Weisheng Dong, Xidian University, China
Alexey Dosovitskiy, Intel Labs
Touradj Ebrahimi, EPFL, Switzerland
Michael Elad, Technion, Israel
Corneliu Florea, University Politehnica of Bucharest, Romania
Alessandro Foi, Tampere University of Technology, Finland
Peter Gehler, University of Tübingen, MPI Intelligent Systems, Amazon, Germany
Bastian Goldluecke, University of Konstanz, Germany
Luc Van Gool, ETH Zürich and KU Leuven, Belgium
Shuhang Gu, ETH Zürich, Switzerland
Michael Hirsch, Amazon
Hiroto Honda, DeNA Co., Japan
Jia-Bin Huang, Virginia Tech, US
Michal Irani, Weizmann Institute, Israel
Phillip Isola, UC Berkeley, US
Zhe Hu,
Sing Bing Kang, Microsoft Research, US
Jan Kautz, NVIDIA Research, US
Seon Joo Kim, Yonsei University, Korea
Vivek Kwatra, Google
In So Kweon, KAIST, Korea
Christian Ledig, Twitter Inc.
Kyoung Mu Lee, Seoul National University, South Korea
Seungyong Lee, POSTECH, South Korea
Stephen Lin, Microsoft Research Asia
Chen Change Loy, Chinese University of Hong Kong
Vladimir Lukin, National Aerospace University, Ukraine
Kai-Kuang Ma, Nanyang Technological University, Singapore
Vasile Manta, Technical University of Iasi, Romania
Yasuyuki Matsushita, Osaka University, Japan
Peyman Milanfar, Google and UCSC, US
Rafael Molina Soriano, University of Granada, Spain
Yusuke Monno, Tokyo Institute of Technology, Japan
Hajime Nagahara, Osaka University, Japan
Vinay P. Namboodiri, IIT Kanpur, India
Sebastian Nowozin, Microsoft Research Cambridge, UK
Federico Perazzi, Disney Research
Aleksandra Pizurica, Ghent University, Belgium
Sylvain Paris, Adobe
Fatih Porikli, Australian National University, NICTA, Australia
Hayder Radha, Michigan State University, US
Tobias Ritschel, University College London, UK
Antonio Robles-Kelly, CSIRO, Australia
Stefan Roth, TU Darmstadt, Germany
Aline Roumy, INRIA, France
Jordi Salvador, Amazon, US
Yoichi Sato, University of Tokyo, Japan
Konrad Schindler, ETH Zurich, Switzerland
Samuel Schulter, NEC Labs America
Nicu Sebe, University of Trento, Italy
Eli Shechtman, Adobe Research, US
Boxin Shi, National Institute of Advanced Industrial Science and Technology (AIST), Japan
Wenzhe Shi, Twitter Inc.
Alexander Sorkine-Hornung, Disney Research
Sabine Süsstrunk, EPFL, Switzerland
Yu-Wing Tai, Tencent Youtu
Hugues Talbot, Université Paris Est, France
Robby T. Tan, Yale-NUS College, Singapore
Masayuki Tanaka, Tokyo Institute of Technology, Japan
Jean-Philippe Tarel, IFSTTAR, France
Radu Timofte, ETH Zürich, Switzerland
George Toderici, Google, US
Ashok Veeraraghavan, Rice University, US
Jue Wang, Megvii Research, US
Chih-Yuan Yang, UC Merced, US
Jianchao Yang, Snapchat
Ming-Hsuan Yang, University of California at Merced, US
Qingxiong Yang, Didi Chuxing, China
Jong Chul Ye, KAIST, Korea
Jason Yosinski, Uber AI Labs, US
Wenjun Zeng, Microsoft Research
Lei Zhang, The Hong Kong Polytechnic University
Wangmeng Zuo, Harbin Institute of Technology, China


Paolo Favaro, University of Bern
Peyman Milanfar, Google
Tero Karras, Nvidia
Jun-Yan Zhu, MIT
Sylvain Paris, Adobe
Chen Change Loy, Nanyang Technological University
Chiu Man Ho, OPPO


Adobe Research
ETH Zurich / CVL


Email: radu.timofte [at]

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