Image Shadow Removal

15 papers with code • 0 benchmarks • 1 datasets

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Most implemented papers

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.

Robust Graph Learning from Noisy Data

sckangz/RGC 17 Dec 2018

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.

Mask-ShadowNet: Towards Shadow Removal via Masked Adaptive Instance Normalization

penguinbing/Mask-ShadowNet 19 Apr 2021

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.

ShaDocNet: Learning Spatial-Aware Tokens in Transformer for Document Shadow Removal

CXH-Research/ShadocNet 30 Nov 2022

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.

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.