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20162024
most citedR2RNet: Low-light Image Enhancement via Real-low to Real-normal Network

411 citations · 2k across the 20 of their papers we have counts for

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Showing 2021Show all

5 papers · 1 filter

eess.IV2021★ 17 cited

Implicit Neural Representations for Image Compression

Yannick Strümpler, Janis Postels, Ren Yang +2

Recently Implicit Neural Representations (INRs) gained attention as a novel and effective representation for various data types. Thus far, prior work mostly focused on optimizing t…

eess.IV2021★ 5 cited

Perceptual Learned Video Compression with Recurrent Conditional GAN

Ren Yang, Radu Timofte, Luc Van Gool

This paper proposes a Perceptual Learned Video Compression (PLVC) approach with recurrent conditional GAN. We employ the recurrent auto-encoder-based compression network as the gen…

cs.CV2021★ 411 cited

R2RNet: Low-light Image Enhancement via Real-low to Real-normal Network

Jiang Hai, Zhu Xuan, Songchen Han +4

Images captured in weak illumination conditions could seriously degrade the image quality. Solving a series of degradation of low-light images can effectively improve the visual qu…

eess.IV2021★ 1 cited

NTIRE 2021 Challenge on Quality Enhancement of Compressed Video: Dataset and Study

Ren Yang, Radu Timofte

This paper introduces a novel dataset for video enhancement and studies the state-of-the-art methods of the NTIRE 2021 challenge on quality enhancement of compressed video. The cha…

eess.IV2021★ 4 cited

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

Ren Yang, Radu Timofte, Jing Liu +69

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 Di…