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
Robust Graph Learning from Noisy Data
The proposed model is able to boost the performance of data clustering, semisupervised classification, and data recovery significantly, primarily due to two key factors: 1) enhanced low-rank recovery by exploiting the graph smoothness assumption, 2) improved graph construction by exploiting clean data recovered by robust PCA.
BEDSR-Net: A Deep Shadow Removal Network From a Single Document Image
IsHYuhi/BEDSR-Net_A_Deep_Shadow_Removal_Network_from_a_Single_Document_Image
•
•
CVPR 2020
For taking advantage of specific properties of document images, a background estimation module is designed for extracting the global background color of the document.
Auto-Exposure Fusion for Single-Image Shadow Removal
tsingqguo/exposure-fusion-shadow-removal
•
•
CVPR 2021
We conduct extensive experiments on the ISTD, ISTD+, and SRD datasets to validate our method's effectiveness and show better performance in shadow regions and comparable performance in non-shadow regions over the state-of-the-art methods.
Efficient Model-Driven Network for Shadow Removal
zhuyr97/AAAI2022_Unfolding_Network_Shadow_Removal
•
•
AAAI 2022
To address these issues, we first propose a new shadow illumination model for the shadow removal task.
High-Resolution Document Shadow Removal via A Large-Scale Real-World Dataset and A Frequency-Aware Shadow Erasing Net
CXH-Research/DocShadow-SD7K
•
•
ICCV 2023
We handle high-resolution document shadow removal directly via a larger-scale real-world dataset and a carefully designed frequency-aware network.
Mask-ShadowNet: Towards Shadow Removal via Masked Adaptive Instance Normalization
penguinbing/Mask-ShadowNet
•
•
Shadow removal is an important yet challenging task in image processing and computer vision.
DC-ShadowNet: Single-Image Hard and Soft Shadow Removal Using Unsupervised Domain-Classifier Guided Network
jinyeying/DC-ShadowNet-Hard-and-Soft-Shadow-Removal
•
•
ICCV 2021
To address the problem, in this paper, we propose an unsupervised domain-classifier guided shadow removal network, DC-ShadowNet.
DeS3: Adaptive Attention-driven Self and Soft Shadow Removal using ViT Similarity
Most existing methods rely on binary shadow masks, without considering the ambiguous boundaries of soft and self shadows.
ShaDocNet: Learning Spatial-Aware Tokens in Transformer for Document Shadow Removal
Shadow removal improves the visual quality and legibility of digital copies of documents.
ShadowDiffusion: When Degradation Prior Meets Diffusion Model for Shadow Removal
GuoLanqing/ShadowDiffusion
•
•
CVPR 2023
Recent deep learning methods have achieved promising results in image shadow removal.
