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NTIRE 2017 : CVPR 2017- New Trends in Image Restoration and Enhancement workshop and challenge on image super-resolution | |||||||||||||||
Link: http://www.vision.ee.ethz.ch/ntire17/ | |||||||||||||||
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Call For Papers | |||||||||||||||
NTIRE: New Trends in Image Restoration and Enhancement workshop and challenge on image super-resolution 2017
In conjunction with CVPR 2017 Website: http://www.vision.ee.ethz.ch/ntire17/ Contact: radu.timofte [at] vision.ee.ethz.ch Scope Image restoration and image enhancement are key computer vision tasks, aiming at the restoration of degraded image content or the filling in of missing information. 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, with image restoration or enhancement serving 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. 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. Topics Papers addressing topics related to image restoration and enhancement are invited. The topics include, but are not limited to: ● Image inpainting ● Image deblurring ● Image denoising ● Image upsampling and super-resolution ● Image filtering ● Image dehazing ● Demosaicing ● Image enhancement: brightening, color adjustment, sharpening, etc. ● Style transfer ● Image generation and image hallucination ● Image-quality assessment ● Video restoration and enhancement ● Hyperspectral imaging ● Methods robust to changing weather conditions ● Studies and applications of the above. Submission 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. http://cvpr2017.thecvf.com/submission/main_conference/author_guidelines 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. https://cmt3.research.microsoft.com/NTIRE2017 Accepted and presented papers will be published after the conference in the CVPR Workshops Proceedings on by IEEE (http://www.ieee.org) and Computer Vision Foundation (www.cv-foundation.org). 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: http://cvpr2017.thecvf.com/files/cvpr2017AuthorKit.zip Workshop Dates ● Submission Deadline: April 24, 2017 (extended!) ● Decisions: May 08, 2017 ● Camera Ready Deadline: May 18, 2017 Challenge on Example-based Single-Image Super-Resolution In order to gauge the current state-of-the-art in example-based single-image super-resolution, to compare and to promote different solutions we are organizing an NTIRE challenge in conjunction with the CVPR 2017 conference. We propose a large DIV2K dataset with DIVerse 2K resolution images. The challenge has 2 tracks: ● Track 1: bicubic uses the bicubic downscaling (Matlab imresize), one of the most common settings from the recent single-image super-resolution literature. ● Track 2: unknown assumes that the explicit forms for the degradation operators are unknown, only the training pairs of low and high images are available. To learn more about the challenge, to participate in the challenge, and to access the newly collected DIV2K dataset with DIVerse 2K resolution images everybody is invited to register at the links from: http://www.vision.ee.ethz.ch/ntire17/ The training data is already made available to the registered participants. Challenge Dates ● Release of train data: February 14, 2017 ● Validation server online: February 25, 2017 ● Competition ends: April 16, 2017 (extended!) Organizers ● Radu Timofte, ETH Zurich, Switzerland (radu.timofte [at] vision.ee.ethz.ch) ● Ming-Hsuan Yang, University of California at Merced, US (mhyang [at] ucmerced.edu) ● Eirikur Agustsson, ETH Zurich, Switzerland (eirikur.agustsson [at] vision.ee.ethz.ch) ● Lei Zhang, The Hong Kong Polytechnic University (cslzhang [at] polyu.edu.hk) ● Luc Van Gool, KU Leuven, Belgium and ETH Zurich, Switzerland (vangool [at] vision.ee.ethz.ch) Program Committee Cosmin Ancuti, Université catholique de Louvain (UCL), Belgium Michael S. Brown, York University, Canada Subhasis Chaudhuri, IIT Bombay, India Sunghyun Cho, Samsung Oliver Cossairt, Northwestern University, US 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 Bastian Goldluecke, University of Konstanz, Germany Luc Van Gool, ETH Zürich and KU Leuven, Belgium Peter Gehler, University of Tübingen and MPI Intelligent Systems, Germany Hiroto Honda, DeNA Co., Japan Michal Irani, Weizmann Institute, Israel Phillip Isola, UC Berkeley, US Zhe Hu, Light.co Sing Bing Kang, Microsoft Research, US Vivek Kwatra, Google 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, Kyushu University, Japan Vinay P. Namboodiri, IIT Kanpur, India Sebastian Nowozin, Microsoft Research Cambridge, UK Aleksandra Pizurica, Ghent University, Belgium Fatih Porikli, Australian National University, NICTA, Australia Hayder Radha, Michigan State University, US Stefan Roth, TU Darmstadt, Germany Aline Roumy, INRIA, France Jordi Salvador, Amazon, US Yoichi Sato, University of Tokyo, Japan Samuel Schulter, NEC Labs America Nicu Sebe, University of Trento, Italy 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 Ashok Veeraraghavan, Rice University, US Jue Wang, Megvii Research, US Chih-Yuan Yang, UC Merced, US Ming-Hsuan Yang, University of California at Merced, US Qingxiong Yang, Didi Chuxing, China Lei Zhang, The Hong Kong Polytechnic University Wangmeng Zuo, Harbin Institute of Technology, China Speakers Alexei Efros, UC Berkeley, US Jan Kautz, NVIDIA Liang Lin, SenseTime and Sun Yat-Sen University, China Peyman Milanfar, Google and UC Santa Cruz, US Eli Shechtman, Adobe Wenzhe Shi, Twitter Inc. Sabine Süsstrunk, EPFL, Switzerland Sponsors NVIDIA SenseTime Twitter Inc Contact Email: radu.timofte [at] vision.ee.ethz.ch Website: http://www.vision.ee.ethz.ch/ntire17/ |
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