Results 21 to 30 of about 19,217 (260)
Shadow Removal in Vehicle Detection Using ResUNet-a [PDF]
Iranica Journal of Energy and Environment, 2023 In traffic monitoring for video analysis systems, vehicle shadows have a negative effect on their performance. Shadow detection and removal are essential steps in accurate vehicle detection.
Z. Dorrani, H. Farsi, S. Mohamadzadeh
doaj +1 more source
REMOVING SHADOWS FROM HIGH-RESOLUTION URBAN AERIAL IMAGES BASED ON COLOR CONSTANCY [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2012 A method is explored to remove tall building shadows in true color and color infrared urban aerial images based on the theory of color constancy. This paper first uses the specthem ratio and Otsu threshold segmentation methods to detect building shadows ...
Q. Ye, H. Xie, Q. Xu
doaj +1 more source
UnShadowNet: Illumination Critic Guided Contrastive Learning for Shadow Removal
IEEE Access, 2023 Shadows are frequently encountered natural phenomena that significantly hinder the performance of computer vision perception systems in practical settings, e.g., autonomous driving.
Subhrajyoti Dasgupta +6 more
doaj +1 more source
Learning to Remove Soft Shadows [PDF]
ACM Transactions on Graphics, 2015 Manipulated images lose believability if the user's edits fail to account for shadows. We propose a method that makes removal and editing of soft shadows easy. Soft shadows are ubiquitous, but remain notoriously difficult to extract and manipulate. We posit that soft shadows can be segmented, and therefore edited, by learning a mapping function for ...
Maciej Gryka +2 more
openaire +1 more source
Self-Supervised Shadow Removal
CoRR, 2020 10 pages, 4 figures, 6 ...
Florin-Alexandru Vasluianu +3 more
openaire +2 more sources
CNSNet: A Cleanness-Navigated-Shadow Network for Shadow Removal
, 2023 Accepted in ECCVW ...
Qianhao Yu +3 more
openaire +2 more sources
Texture-Consistent Shadow Removal [PDF]
, 2008 This paper presents an approach to shadow removal that preserves texture consistency between the original shadow and lit area. Illumination reduction in the shadow area not only darkens that area, but also changes the texture characteristics there.
Feng Liu 0015, Michael Gleicher
openaire +1 more source
Single image shadow removal by optimization using non-shadow anchor values
Computational Visual Media, 2019 Shadow removal has evolved as a pre-processing step for various computer vision tasks. Several studies have been carried out over the past two decades to eliminate shadows from videos and images. Accurate shadow detection is an open problem because it is
Saritha Murali +2 more
doaj +1 more source
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
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