NTIRE 2021 Challenge for Defocus Deblurring Using Dual-pixel Images: Methods and Results

Abuolaim, Abdullah; Timofte, Radu; Brown, Michael S.; Zhang, Dafeng; Wang, Xiaobing; Zamir, Syed Waqas; Arora, Aditya; Khan, Salman; Hayat, Munawar; Khan, Fahad Shahbaz; Shao, Ling; Liu, Shuai; Lei, Lei; Feng, Chaoyu; Xiong, Zhiwei; Xiao, Zeyu; Xu, Ruikang; Zhu, Yunan; Liu, Dong; Vo, Tu; Miao, Si; Shah, Nisarg; Liang, Pengwei; Zhong, Zhang; Chen, Yiqun; Li, Chenghua; Bai, Xiaoying; Zhang, Chi; Yao, Yiheng; Gang, Ruipeng; Nathan, Sabari; Ragavendran, Thangavelu; Srinija, Venkatakrishnan; Srivatsav, Venkatakrishnan

doi:10.1109/cvprw53098.2021.00070

Cited by 17 publications

(9 citation statements)

References 19 publications

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“…This challenge is one of the NTIRE 2021 associated challenges: nonhomogeneous dehazing [4], defocus deblurring using dual-pixel [2], depth guided image relighting [16], image deblurring [39], multi-modal aerial view imagery classification [33], learning the super-resolution space [35], quality enhancement of compressed video (this report), video super-resolution [46], perceptual image quality assessment [18], burst super-resolution [5], and high dynamic range imaging [41].…”

Section: Ntire 2021 Challengementioning

confidence: 99%

NTIRE 2021 Challenge on Quality Enhancement of Compressed Video: Methods and Results

Yang¹,

Timofte²,

Liu³

et al. 2021

Preprint

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This paper reviews the first NTIRE challenge on quality enhancement of compressed video, with a focus on the proposed methods and results. In this challenge, the new Large-scale Diverse Video (LDV) dataset is employed. The challenge has three tracks. Tracks 1 and 2 aim at enhancing the videos compressed by HEVC at a fixed QP, while Track 3 is designed for enhancing the videos compressed by x265 at a fixed bit-rate. Besides, the quality enhancement of Tracks 1 and 3 targets at improving the fidelity (PSNR), and Track 2 targets at enhancing the perceptual quality. The three tracks totally attract 482 registrations. In the test phase, 12 teams, 8 teams and 11 teams submitted the final results of Tracks 1, 2 and 3, respectively. The proposed methods and solutions gauge the state-of-the-art of video quality enhancement. The homepage of the challenge: https: //github.com/RenYang-home/NTIRE21_VEnh

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Section: Ntire 2021 Challengementioning

confidence: 99%

NTIRE 2021 Challenge on Quality Enhancement of Compressed Video: Methods and Results

Yang¹,

Timofte²,

Liu³

et al. 2021

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“…The goal of the NTIRE 2021 Challenge on Burst Super-Resolution is to encourage further research in the burst SR task and provide a common benchmark for evaluating different methods. This challenge is one of the NTIRE 2021 associated challenges: nonhomogeneous dehazing [2], defocus deblurring using dual-pixel [1], depth guided image relighting [10], image deblurring [39], multi-modal aerial view imagery classification [30], learning the superresolution space [33], quality enhancement of heavily compressed videos [56], video super-resolution [47], perceptual image quality assessment [12], burst super-resolution, and high dynamic range [42]. The burst super-resolution challenge contained two tracks.…”

Section: Ntire 2021 Challengementioning

confidence: 99%

NTIRE 2021 Challenge on Burst Super-Resolution: Methods and Results

Bhat¹,

Danelljan²,

Radu³

et al. 2021

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This paper reviews the NTIRE2021 challenge on burst super-resolution. Given a RAW noisy burst as input, the task in the challenge was to generate a clean RGB image with 4 times higher resolution. The challenge contained two tracks; Track 1 evaluating on synthetically generated data, and Track 2 using real-world bursts from mobile camera. In the final testing phase, 6 teams submitted results using a diverse set of solutions. The top-performing methods set a new state-of-the-art for the burst super-resolution task. * Goutam Bhat, Martin Danelljan, and Radu Timofte at ETH Zurich are the NTIRE 2021 challenge organizers. The other authors participated in the challenge and are listed alphabetically. Appendix A contains the participants' team names and affiliations. NTIRE 2021 webpage: https://data.vision.ee.ethz.ch/cvl/ntire21/

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“…The NTIRE 2021 HDR Challenge aims at stimulating research for computational HDR imaging, and better understand the state-of-the-art landscape for both single and multiple frame HDR processing. It is part of a wide spectrum of associated challenges with the NTIRE 2021 workshop: non-homogeneous dehazing [3], defocus deblurring using dual-pixel [2], depth guided image relighting [10], image deblurring [25], multi-modal aerial view imagery classification [19], learning the super-resolution space [22], quality enhancement of heavily compressed videos [40], video super-resolution [32], perceptual image quality assessment [12], burst super-resolution [4], high dynamic arXiv:2106.01439v1 [cs.CV] 2 Jun 2021 range [26].…”

Section: Introductionmentioning

confidence: 99%

NTIRE 2021 Challenge on High Dynamic Range Imaging: Dataset, Methods and Results

Pérez-Pellitero

Catley-Chandar

Leonardis

et al. 2021

2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

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This paper reviews the first challenge on high-dynamic range (HDR) imaging that was part of the New Trends in Image Restoration and Enhancement (NTIRE) workshop, held in conjunction with CVPR 2021. This manuscript focuses on the newly introduced dataset, the proposed methods and their results. The challenge aims at estimating a HDR image from one or multiple respective low-dynamic range (LDR) observations, which might suffer from underor over-exposed regions and different sources of noise. The challenge is composed by two tracks: In Track 1 only a single LDR image is provided as input, whereas in Track 2 three differently-exposed LDR images with inter-frame motion are available. In both tracks, the ultimate goal is to achieve the best objective HDR reconstruction in terms of PSNR with respect to a ground-truth image, evaluated both directly and with a canonical tonemapping operation.

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NTIRE 2021 Challenge for Defocus Deblurring Using Dual-pixel Images: Methods and Results

Cited by 17 publications

References 19 publications

NTIRE 2021 Challenge on Quality Enhancement of Compressed Video: Methods and Results

NTIRE 2021 Challenge on Quality Enhancement of Compressed Video: Methods and Results

NTIRE 2021 Challenge on Burst Super-Resolution: Methods and Results

NTIRE 2021 Challenge on High Dynamic Range Imaging: Dataset, Methods and Results

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