Image Shadow Removal
19 papers with code • 0 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in Image Shadow Removal
SD7K
Latest papers
NTIRE 2023 Image Shadow Removal Challenge Technical Report: Team IIM_TTI
Yuki-11/NTIRE2023_ShadowRemoval_IIM_TTI
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In this paper, we analyze and discuss ShadowFormer in preparation for the NTIRE2023 Shadow Removal Challenge [1], implementing five key improvements: image alignment, the introduction of a perceptual quality loss function, the semi-automatic annotation for shadow detection, joint learning of shadow detection and removal, and the introduction of new data augmentation technique "CutShadow" for shadow removal.
High-Resolution Document Shadow Removal via A Large-Scale Real-World Dataset and A Frequency-Aware Shadow Erasing Net
CXH-Research/DocShadow-SD7K
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ICCV 2023
We handle high-resolution document shadow removal directly via a larger-scale real-world dataset and a carefully designed frequency-aware network.
A Shadow Imaging Bilinear Model and Three-branch Residual Network for Shadow Removal
nachifur/TBRNet
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IEEE Transactions on Neural Networks and Learning Systems 2023
Thus, our network ensures the fidelity of nonshadow areas and restores the light intensity of shadow areas through three-branch collaboration.
SAM-helps-Shadow:When Segment Anything Model meet shadow removal
The challenges surrounding the application of image shadow removal to real-world images and not just constrained datasets like ISTD/SRD have highlighted an urgent need for zero-shot learning in this field.
Shadow Removal of Text Document Images Using Background Estimation and Adaptive Text Enhancement
Thirdly, we propose an adaptive text contrast enhancement strategy to generate shadow-free results with comfortable visual perception across shadow and non-shadow regions.
Refusion: Enabling Large-Size Realistic Image Restoration with Latent-Space Diffusion Models
algolzw/image-restoration-sde
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This work aims to improve the applicability of diffusion models in realistic image restoration.
A Decoupled Multi-Task Network for Shadow Removal
nachifur/DMTN
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IEEE Transactions on Multimedia 2023
Last, these features are converted to a target shadow-free image, affiliated shadow matte, and shadow image, supervised by multi-task joint loss functions.
Leveraging Inpainting for Single-Image Shadow Removal
tsingqguo/inpaint4shadow
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ICCV 2023
In this work, we find that pretraining shadow removal networks on the image inpainting dataset can reduce the shadow remnants significantly: a naive encoder-decoder network gets competitive restoration quality w. r. t.
ShadowFormer: Global Context Helps Image Shadow Removal
It is still challenging for the deep shadow removal model to exploit the global contextual correlation between shadow and non-shadow regions.
Document Image Shadow Removal Guided by Color-Aware Background
hyyh1314/BGShadowNet
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CVPR 2023
In this paper, we present a color-aware background extraction network (CBENet) for extracting a spatially varying background image that accurately depicts the background colors of the document.
