Image Shadow Removal
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Benchmarks
INS Dataset
Most implemented
High-Resolution Document Shadow Removal via A Large-Scale Real-World Dataset and A Frequency-Aware Shadow Erasing Net
ShadowFormer: Global Context Helps Image Shadow Removal
Efficient Model-Driven Network for Shadow Removal
Auto-Exposure Fusion for Single-Image Shadow Removal
BEDSR-Net: A Deep Shadow Removal Network From a Single Document Image
Robust Graph Learning from Noisy Data
Papers
deSEO: Physics-Aware Dataset Creation for High-Resolution Satellite Image Shadow Removal
Shadows cast by terrain and tall structures remain a major obstacle for high-resolution satellite image analysis, degrading classification, detection, and 3D reconstruction performance. Public resources offering geometry…
Image Shadow Removal3D ReconstructionShadow DetectionSARU: A Shadow-Aware and Removal Unified Framework for Remote Sensing Images with New Benchmarks
Shadows are a prevalent problem in remote sensing imagery (RSI), degrading visual quality and severely limiting the performance of downstream tasks like object detection and semantic segmentation. Most prior works treat …
Semantic SegmentationImage Shadow RemovalShadow DetectionObject DetectionAeroDeshadow: Physics-Guided Shadow Synthesis and Penumbra-Aware Deshadowing for Aerospace Imagery
Shadows are prevalent in high-resolution aerospace imagery (ASI). They often cause spectral distortion and information loss, which degrade downstream interpretation tasks. While deep learning methods have advanced natura…
Image Shadow RemovalWinner of CVPR2026 NTIRE Challenge on Image Shadow Removal: Semantic and Geometric Guidance for Shadow Removal via Cascaded Refinement
We present a three-stage progressive shadow-removal pipeline for the CVPR2026 NTIRE WSRD+ challenge. Built on OmniSR, our method treats deshadowing as iterative direct refinement, where later stages correct residual arte…
Image Shadow RemovalPhaSR: Generalized Image Shadow Removal with Physically Aligned Priors
Shadow removal under diverse lighting conditions requires disentangling illumination from intrinsic reflectance, a challenge compounded when physical priors are not properly aligned. We propose PhaSR (Physically Aligned …
Image Shadow RemovalDeshadowMamba: Deshadowing as 1D Sequential Similarity
Recent deep models for image shadow removal often rely on attention-based architectures to capture long-range dependencies. However, their fixed attention patterns tend to mix illumination cues from irrelevant regions, l…
Contrastive LearningImage Shadow Removal