NTIRE 2022 Challenge on High Dynamic Range Imaging: Methods and Results
- URL: http://arxiv.org/abs/2205.12633v1
- Date: Wed, 25 May 2022 10:20:06 GMT
- Title: NTIRE 2022 Challenge on High Dynamic Range Imaging: Methods and Results
- Authors: Eduardo P\'erez-Pellitero, Sibi Catley-Chandar, Richard Shaw, Ale\v{s}
Leonardis, Radu Timofte, Zexin Zhang, Cen Liu, Yunbo Peng, Yue Lin, Gaocheng
Yu, Jin Zhang, Zhe Ma, Hongbin Wang, Xiangyu Chen, Xintao Wang, Haiwei Wu,
Lin Liu, Chao Dong, Jiantao Zhou, Qingsen Yan, Song Zhang, Weiye Chen, Yuhang
Liu, Zhen Zhang, Yanning Zhang, Javen Qinfeng Shi, Dong Gong, Dan Zhu, Mengdi
Sun, Guannan Chen, Yang Hu, Haowei Li, Baozhu Zou, Zhen Liu, Wenjie Lin, Ting
Jiang, Chengzhi Jiang, Xinpeng Li, Mingyan Han, Haoqiang Fan, Jian Sun,
Shuaicheng Liu, Juan Mar\'in-Vega, Michael Sloth, Peter Schneider-Kamp,
Richard R\"ottger, Chunyang Li, Long Bao, Gang He, Ziyao Xu, Li Xu, Gen Zhan,
Ming Sun, Xing Wen, Junlin Li, Jinjing Li, Chenghua Li, Ruipeng Gang, Fangya
Li, Chenming Liu, Shuang Feng, Fei Lei, Rui Liu, Junxiang Ruan, Tianhong Dai,
Wei Li, Zhan Lu, Hengyan Liu, Peian Huang, Guangyu Ren, Yonglin Luo, Chang
Liu, Qiang Tu, Fangya Li, Ruipeng Gang, Chenghua Li, Jinjing Li, Sai Ma,
Chenming Liu, Yizhen Cao, Steven Tel, Barthelemy Heyrman, Dominique Ginhac,
Chul Lee, Gahyeon Kim, Seonghyun Park, An Gia Vien, Truong Thanh Nhat Mai,
Howoon Yoon, Tu Vo, Alexander Holston, Sheir Zaheer and Chan Y. Park
- Abstract summary: The challenge was part of the New Trends in Image Restoration and Enhancement (NTIRE) workshop, held in conjunction with CVPR 2022.
The challenge aims at estimating an HDR image from multiple respective low dynamic range (LDR) observations.
- Score: 173.32437855731752
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: This paper reviews the challenge on constrained high dynamic range (HDR)
imaging that was part of the New Trends in Image Restoration and Enhancement
(NTIRE) workshop, held in conjunction with CVPR 2022. This manuscript focuses
on the competition set-up, datasets, the proposed methods and their results.
The challenge aims at estimating an HDR image from multiple respective low
dynamic range (LDR) observations, which might suffer from under- or
over-exposed regions and different sources of noise. The challenge is composed
of two tracks with an emphasis on fidelity and complexity constraints: In Track
1, participants are asked to optimize objective fidelity scores while imposing
a low-complexity constraint (i.e. solutions can not exceed a given number of
operations). In Track 2, participants are asked to minimize the complexity of
their solutions while imposing a constraint on fidelity scores (i.e. solutions
are required to obtain a higher fidelity score than the prescribed baseline).
Both tracks use the same data and metrics: Fidelity is measured by means of
PSNR with respect to a ground-truth HDR image (computed both directly and with
a canonical tonemapping operation), while complexity metrics include the number
of Multiply-Accumulate (MAC) operations and runtime (in seconds).
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