Papers Shadow Detection
“Shadow Detection” 태그가 달린 논문 86편 · 필터 해제
Revisiting Shadow Detection from a Vision-Language Perspective
Shadow detection is commonly formulated as a vision-driven dense prediction problem, where models rely primarily on pixel-wise visual supervision to distinguish shadows from non-shadow regions. However, this formulation …
Shadow DetectiondeSEO: 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 DetectionCast and Attached Shadow Detection via Iterative Light and Geometry Reasoning
Shadows encode rich information about scene geometry and illumination, yet existing methods either predict a unified shadow mask or overlook attached shadows entirely. We address this gap by proposing a framework for joi…
Shadow DetectionSAM3-Adapter: Efficient Adaptation of Segment Anything 3 for Camouflage Object Segmentation, Shadow Detection, and Medical Image Segmentation
The rapid rise of large-scale foundation models has reshaped the landscape of image segmentation, with models such as Segment Anything achieving unprecedented versatility across diverse vision tasks. However, previous ge…
Medical Image SegmentationObject SegmentationShadow DetectionObject DetectionDTTNet: Improving Video Shadow Detection via Dark-Aware Guidance and Tokenized Temporal Modeling
Video shadow detection confronts two entwined difficulties: distinguishing shadows from complex backgrounds and modeling dynamic shadow deformations under varying illumination. To address shadow-background ambiguity, we …
Shadow DetectionDeep Learning for Clouds and Cloud Shadow Segmentation in Methane Satellite and Airborne Imaging Spectroscopy
Effective cloud and cloud shadow detection is a critical prerequisite for accurate retrieval of concentrations of atmospheric methane (CH4) or other trace gases in hyperspectral remote sensing. This challenge is especial…
Shadow DetectionS-EO: A Large-Scale Dataset for Geometry-Aware Shadow Detection in Remote Sensing Applications
We introduce the S-EO dataset: a large-scale, high-resolution dataset, designed to advance geometry-aware shadow detection. Collected from diverse public-domain sources, including challenge datasets and government provid…
3D ReconstructionNeRFShadow DetectionFastInstShadow: A Simple Query-Based Model for Instance Shadow Detection
Instance shadow detection is the task of detecting pairs of shadows and objects, where existing methods first detect shadows and objects independently, then associate them. This paper introduces FastInstShadow, a method …
DecoderInstance Shadow DetectionShadow DetectionQDCNN: Quantum Deep Learning for Enhancing Safety and Reliability in Autonomous Transportation Systems
In transportation cyber-physical systems (CPS), ensuring safety and reliability in real-time decision-making is essential for successfully deploying autonomous vehicles and intelligent transportation networks. However, t…
Autonomous VehiclesComputational EfficiencyShadow DetectionWhen SAM2 Meets Video Shadow and Mirror Detection
As the successor to the Segment Anything Model (SAM), the Segment Anything Model 2 (SAM2) not only improves performance in image segmentation but also extends its capabilities to video segmentation. However, its effectiv…
Image SegmentationMirror DetectionSegmentationSemantic Segmentation+4MetaShadow: Object-Centered Shadow Detection, Removal, and Synthesis
Shadows are often under-considered or even ignored in image editing applications, limiting the realism of the edited results. In this paper, we introduce MetaShadow, a three-in-one versatile framework that enables detect…
ObjectShadow DetectionShadow Detection And RemovalTest-Time Intensity Consistency Adaptation for Shadow Detection
Shadow detection is crucial for accurate scene understanding in computer vision, yet it is challenged by the diverse appearances of shadows caused by variations in illumination, object geometry, and scene context. Deep l…
DecoderDiversityScene UnderstandingShadow Detection+1Unveiling Deep Shadows: A Survey and Benchmark on Image and Video Shadow Detection, Removal, and Generation in the Deep Learning Era
Shadows are created when light encounters obstacles, resulting in regions of reduced illumination. In computer vision, detecting, removing, and generating shadows are critical tasks for improving scene understanding, enh…
Scene UnderstandingShadow DetectionSurveyVideo Editing+1RenDetNet: Weakly-supervised Shadow Detection with Shadow Caster Verification
Existing shadow detection models struggle to differentiate dark image areas from shadows. In this paper, we tackle this issue by verifying that all detected shadows are real, i.e. they have paired shadow casters. We perf…
Shadow DetectionTimeline and Boundary Guided Diffusion Network for Video Shadow Detection
Video Shadow Detection (VSD) aims to detect the shadow masks with frame sequence. Existing works suffer from inefficient temporal learning. Moreover, few works address the VSD problem by considering the characteristic (i…
Shadow DetectionVideo Shadow DetectionLanguage-Driven Interactive Shadow Detection
Traditional shadow detectors often identify all shadow regions of static images or video sequences. This work presents the Referring Video Shadow Detection (RVSD), which is an innovative task that rejuvenates the classic…
DescriptiveShadow DetectionVideo EditingVideo Shadow DetectionSAM2-Adapter: Evaluating & Adapting Segment Anything 2 in Downstream Tasks: Camouflage, Shadow, Medical Image Segmentation, and More
The advent of large models, also known as foundation models, has significantly transformed the AI research landscape, with models like Segment Anything (SAM) achieving notable success in diverse image segmentation scenar…
Image SegmentationMedical Image Segmentationobject-detectionObject Detection+4SwinShadow: Shifted Window for Ambiguous Adjacent Shadow Detection
Shadow detection is a fundamental and challenging task in many computer vision applications. Intuitively, most shadows come from the occlusion of light by the object itself, resulting in the object and its shadow being c…
Shadow DetectionCloudS2Mask: A novel deep learning approach for improved cloud and cloud shadow masking in Sentinel-2 imagery
The Sentinel-2 satellite constellation produces high-resolution multispectral data, covering the entire Earth's land surface every five days. However, the use of this data is significantly impacted by the presence of pix…
Active LearningShadow DetectionTransfer Learning