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20202026
most citedShadowFormer: Global Context Helps Image Shadow Removal

14 citations · 48 across the 26 of their papers we have counts for

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Showing 2023Show all

6 papers · 1 filter

cs.CV2023★ 4 cited

SinSR: Diffusion-Based Image Super-Resolution in a Single Step

Yufei Wang, Wenhan Yang, Xinyuan Chen +7

While super-resolution (SR) methods based on diffusion models exhibit promising results, their practical application is hindered by the substantial number of required inference ste…

cs.CV2023★ 3 cited

ExposureDiffusion: Learning to Expose for Low-light Image Enhancement

Yufei Wang, Yi Yu, Wenhan Yang +4

Previous raw image-based low-light image enhancement methods predominantly relied on feed-forward neural networks to learn deterministic mappings from low-light to normally-exposed…

cs.CV2023

Beyond Learned Metadata-based Raw Image Reconstruction

Yufei Wang, Yi Yu, Wenhan Yang +4

While raw images have distinct advantages over sRGB images, e.g., linearity and fine-grained quantization levels, they are not widely adopted by general users due to their substant…

eess.IV2023

Unsupervised Deep Digital Staining For Microscopic Cell Images Via Knowledge Distillation

Ziwang Xu, Lanqing Guo, Shuyan Zhang +2

Staining is critical to cell imaging and medical diagnosis, which is expensive, time-consuming, labor-intensive, and causes irreversible changes to cell tissues. Recent advances in…

cs.CV2023

Raw Image Reconstruction with Learned Compact Metadata

Yufei Wang, Yi Yu, Wenhan Yang +4

While raw images exhibit advantages over sRGB images (e.g., linearity and fine-grained quantization level), they are not widely used by common users due to the large storage requir…

cs.CV2023★ 14 cited

ShadowFormer: Global Context Helps Image Shadow Removal

Lanqing Guo, Siyu Huang, Ding Liu +2

Recent deep learning methods have achieved promising results in image shadow removal. However, most of the existing approaches focus on working locally within shadow and non-shadow…