Image Shadow Removal
19 papers with code • 0 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in Image Shadow Removal
SD7K
Most implemented papers
Document Image Shadow Removal Guided by Color-Aware Background
hyyh1314/BGShadowNet
•
•
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.
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.
Leveraging Inpainting for Single-Image Shadow Removal
tsingqguo/inpaint4shadow
•
•
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.
A Decoupled Multi-Task Network for Shadow Removal
nachifur/DMTN
•
•
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.
Refusion: Enabling Large-Size Realistic Image Restoration with Latent-Space Diffusion Models
algolzw/image-restoration-sde
•
•
This work aims to improve the applicability of diffusion models in realistic image restoration.
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.
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.
A Shadow Imaging Bilinear Model and Three-branch Residual Network for Shadow Removal
nachifur/TBRNet
•
•
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.
NTIRE 2023 Image Shadow Removal Challenge Technical Report: Team IIM_TTI
Yuki-11/NTIRE2023_ShadowRemoval_IIM_TTI
•
•
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.
