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20172023
most citedDeep Fourier Up-Sampling

28 citations · 116 across the 18 of their papers we have counts for

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21 papers · 1 filter

cs.CV2023

Learning Image-Adaptive Codebooks for Class-Agnostic Image Restoration

Kechun Liu, Yitong Jiang, Inchang Choi +1

Recent work on discrete generative priors, in the form of codebooks, has shown exciting performance for image reconstruction and restoration, as the discrete prior space spanned by…

cs.CV2022

Overexposure Mask Fusion: Generalizable Reverse ISP Multi-Step Refinement

Jinha Kim, Jun Jiang, Jinwei Gu

With the advent of deep learning methods replacing the ISP in transforming sensor RAW readings into RGB images, numerous methodologies solidified into real-life applications. Equal…

cs.CV20221 cited

Neighbourhood Representative Sampling for Efficient End-to-end Video Quality Assessment

Haoning Wu, Chaofeng Chen, Liang Liao +5

The increased resolution of real-world videos presents a dilemma between efficiency and accuracy for deep Video Quality Assessment (VQA). On the one hand, keeping the original reso…

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…

cs.CV2022

MIPI 2022 Challenge on RGBW Sensor Re-mosaic: Dataset and Report

Qingyu Yang, Guang Yang, Jun Jiang +7

Developing and integrating advanced image sensors with novel algorithms in camera systems are prevalent with the increasing demand for computational photography and imaging on mobi…

cs.CV2022

MIPI 2022 Challenge on RGB+ToF Depth Completion: Dataset and Report

Wenxiu Sun, Qingpeng Zhu, Chongyi Li +6

Developing and integrating advanced image sensors with novel algorithms in camera systems is prevalent with the increasing demand for computational photography and imaging on mobil…