Results 31 to 40 of about 19,948 (258)
Fine-Context Shadow Detection using Shadow Removal
2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2023 Current shadow detection methods perform poorly when detecting shadow regions that are small, unclear or have blurry edges. In this work, we attempt to address this problem on two fronts. First, we propose a Fine Context-aware Shadow Detection Network (FCSD-Net), where we constraint the receptive field size and focus on low-level features to learn fine
Jeya Maria Jose Valanarasu +1 more
openaire +2 more sources
Removing Shadows from Images [PDF]
, 2002 Illumination conditions cause problems for many computer vision algorithms. In particular, shadows in an image can cause segmentation, tracking, or recognition algorithms to fail. In this paper we propose a method to process a 3-band colour image to locate, and subsequently remove shadows.
Finlayson, Graham D. +2 more
openaire +3 more sources
Soft–Hard Attention U-Net Model and Benchmark Dataset for Multiscale Image Shadow Removal
IEEE AccessEffective shadow removal is pivotal in enhancing visual image quality in applications such as computer vision and digital photography. During the last decades physics-based and machine learning methodologies have been proposed; however, most of them have
Eirini Cholopoulou +3 more
doaj +1 more source
Local Water-Filling Algorithm for Shadow Detection and Removal of Document Images
Sensors, 2020 Shadow detection and removal is an important task for digitized document applications. It is hard for many methods to distinguish shadow from printed text due to the high darkness similarity.
Bingshu Wang, C. L. Philip Chen
doaj +1 more source
Shadow Removal for Enhanced Nighttime Driving Scene Generation
Applied SciencesAutonomous vehicles depend on robust vision systems capable of performing under diverse lighting conditions, yet existing models often exhibit substantial performance degradation when applied to nighttime scenarios after being trained exclusively on ...
Heejun Yang, Oh-Hyeon Choung, Yuseok Ban
doaj +1 more source
Shadow Detection Based on Regions of Light Sources for Object Extraction in Nighttime Video
Sensors, 2017 Intelligent video surveillance systems detect pre-configured surveillance events through background modeling, foreground and object extraction, object tracking, and event detection.
Gil-beom Lee +4 more
doaj +1 more source
IEEE AccessThe presence of image shadows significantly impacts the practical applications of computer vision tasks in real-world environments. For example, image recognition, and image segmentation.
Lanfei Zhao, Qiye Wang
doaj +1 more source
deSEO: Physics-Aware Dataset Creation for High-Resolution Satellite Image Shadow Removal [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information SciencesShadows cast by terrain and tall structures remain a major obstacle for high-resolution satellite image analysis, degrading classification, detection, and 3D reconstruction performance.
L. Beltrame +9 more
doaj +1 more source
A Computer Vision Sensor for Efficient Object Detection Under Varying Lighting Conditions
Advanced Intelligent Systems, 2021 Convolutional neural networks (CNNs) have attracted much attention in recent years due to their outstanding performance in image classification. However, changes in lighting conditions can corrupt image segmentation conducted by CNN, leading to false ...
Can Cuhadar +2 more
doaj +1 more source
Regional Attention For Shadow Removal
Proceedings of the 32nd ACM International Conference on MultimediaShadow, as a natural consequence of light interacting with objects, plays a crucial role in shaping the aesthetics of an image, which however also impairs the content visibility and overall visual quality. Recent shadow removal approaches employ the mechanism of attention, due to its effectiveness, as a key component.
Hengxing Liu +2 more
openaire +2 more sources