Papers Image Shadow Removal
“Image Shadow Removal” 태그가 달린 논문 47편 · 필터 해제
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 RemovalElucidating the Design Space of Arbitrary-Noise-Based Diffusion Models
Although EDM aims to unify the design space of diffusion models, its reliance on fixed Gaussian noise prevents it from explaining emerging flow-based methods that diffuse arbitrary noise. Moreover, our study reveals that…
Medical Image DenoisingImage Shadow RemovalImage RestorationDenseSR: Image Shadow Removal as Dense Prediction
Shadows are a common factor degrading image quality. Single-image shadow removal (SR), particularly under challenging indirect illumination, is hampered by non-uniform content degradation and inherent ambiguity. Conseque…
Image Shadow RemovalScene UnderstandingDocShaDiffusion: Diffusion Model in Latent Space for Document Image Shadow Removal
Document shadow removal is a crucial task in the field of document image enhancement. However, existing methods tend to remove shadows with constant color background and ignore color shadows. In this paper, we first desi…
Image Shadow RemovalImage EnhancementTowards Hard and Soft Shadow Removal via Dual-Branch Separation Network and Vision Transformer
Image shadow removal is a crucial task in computer vision. In real-world scenes, shadows alter image color and brightness, posing challenges for perception and texture recognition. Traditional and deep learning methods o…
Image Shadow RemovalShadow RemovalSoftShadow: Leveraging Soft Masks for Penumbra-Aware Shadow Removal
Recent advancements in deep learning have yielded promising results for the image shadow removal task. However, most existing methods rely on binary pre-generated shadow masks. The binary nature of such masks could p…
Image Shadow RemovalShadow RemovalControlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation
Large-scale generative models have achieved remarkable advancements in various visual tasks, yet their application to shadow removal in images remains challenging. These models often generate diverse, realistic details w…
Image ReconstructionImage Shadow RemovalShadow RemovalShadowMamba: State-Space Model with Boundary-Region Selective Scan for Shadow Removal
Image shadow removal is a typical low-level vision problem, where the presence of shadows leads to abrupt changes in brightness in certain regions, affecting the accuracy of upstream tasks. Current shadow removal methods…
Image Shadow RemovalMambaShadow RemovalOmniSR: Shadow Removal under Direct and Indirect Lighting
Shadows can originate from occlusions in both direct and indirect illumination. Although most current shadow removal research focuses on shadows caused by direct illumination, shadows from indirect illumination are often…
Image Shadow RemovalShadow RemovalSoftShadow: Leveraging Penumbra-Aware Soft Masks for Shadow Removal
Recent advancements in deep learning have yielded promising results for the image shadow removal task. However, most existing methods rely on binary pre-generated shadow masks. The binary nature of such masks could poten…
Image Shadow RemovalShadow RemovalSoft-Hard Attention U-Net Model and Benchmark Dataset for Multiscale Image Shadow Removal
Effective shadow removal is pivotal in enhancing the visual quality of images in various applications, ranging from computer vision to digital photography. During the last decades physics and machine learning -based meth…
BenchmarkingHard AttentionImage Shadow RemovalPrivacy Preserving+1Single-Image Shadow Removal Using Deep Learning: A Comprehensive Survey
Shadow removal aims at restoring the image content within shadow regions, pursuing a uniform distribution of illumination that is consistent between shadow and non-shadow regions. {Comparing to other image restoration ta…
Deep LearningImage RestorationImage Shadow RemovalShadow RemovalShadowRefiner: Towards Mask-free Shadow Removal via Fast Fourier Transformer
Shadow-affected images often exhibit pronounced spatial discrepancies in color and illumination, consequently degrading various vision applications including object detection and segmentation systems. To effectively elim…
Image Shadow Removalobject-detectionObject DetectionRepresentation Learning+1Benchmarking Adversarial Robustness of Image Shadow Removal with Shadow-adaptive Attacks
Shadow removal is a task aimed at erasing regional shadows present in images and reinstating visually pleasing natural scenes with consistent illumination. While recent deep learning techniques have demonstrated impressi…
Adversarial AttackAdversarial RobustnessBenchmarkingImage Shadow Removal+1NTIRE 2023 Image Shadow Removal Challenge Technical Report: Team 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 functio…
Data AugmentationImage Shadow RemovalShadow DetectionShadow Detection And Removal+1