NTIRE 2021 Challenge on High Dynamic Range Imaging: Dataset, Methods and Results
원문 초록
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 under- or 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.
함께 살펴볼 논문
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LD-RPS: Zero-Shot Unified Image Restoration via Latent Diffusion Recurrent Posterior Sampling
EAMamba: Efficient All-Around Vision State Space Model for Image Restoration
Visual-Instructed Degradation Diffusion for All-in-One Image Restoration
Unsupervised Imaging Inverse Problems with Diffusion Distribution Matching
Boosting All-in-One Image Restoration via Self-Improved Privilege Learning
IRBridge: Solving Image Restoration Bridge with Pre-trained Generative Diffusion Models
토론
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