most citedDeep Fourier Up-Sampling

28 citations · 36 across the 2 of their papers we have counts for

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cs.CV20231 cited

Learned Image Reasoning Prior Penetrates Deep Unfolding Network for Panchromatic and Multi-Spectral Image Fusion

Man Zhou, Jie Huang, Naishan Zheng +1

The success of deep neural networks for pan-sharpening is commonly in a form of black box, lacking transparency and interpretability. To alleviate this issue, we propose a novel mo…

cs.CV2023

Make Explicit Calibration Implicit: Calibrate Denoiser Instead of the Noise Model

Xin Jin, Jia-Wen Xiao, Ling-Hao Han +4

Explicit calibration-based methods have dominated RAW image denoising under extremely low-light environments. However, these methods are impeded by several critical limitations: a)…

cs.CV2023

Decomposition Ascribed Synergistic Learning for Unified Image Restoration

Jinghao Zhang, Feng Zhao

Learning to restore multiple image degradations within a single model is quite beneficial for real-world applications. Nevertheless, existing works typically concentrate on regardi…

cs.CV20228 cited

Panchromatic and Multispectral Image Fusion via Alternating Reverse Filtering Network

Keyu Yan, Man Zhou, Jie Huang +4

Panchromatic (PAN) and multi-spectral (MS) image fusion, named Pan-sharpening, refers to super-resolve the low-resolution (LR) multi-spectral (MS) images in the spatial domain to g…

cs.CV202228 cited

Deep Fourier Up-Sampling

Man Zhou, Hu Yu, Jie Huang +5

Existing convolutional neural networks widely adopt spatial down-/up-sampling for multi-scale modeling. However, spatial up-sampling operators (\emph{e.g.}, interpolation, transpos…