DSNet: Deep Shadow Network for Illumination Estimation

Author(s):  
Yuan Xiong ◽  
Hongrui Chen ◽  
Jingru Wang ◽  
Zhe Zhu ◽  
Zhong Zhou
2016 ◽  
Vol 2016 (20) ◽  
pp. 1-8 ◽  
Author(s):  
Xiaochuan Chen ◽  
MarkS. Drew ◽  
Ze-Nian Li ◽  
GrahamD. Finlayson

2018 ◽  
Vol 2018 (13) ◽  
pp. 389-1-389-5
Author(s):  
Soonyoung Hong ◽  
Minsub Kim ◽  
Moon Gi Kang

2020 ◽  
Vol 64 (5) ◽  
pp. 50411-1-50411-8
Author(s):  
Hoda Aghaei ◽  
Brian Funt

Abstract For research in the field of illumination estimation and color constancy, there is a need for ground-truth measurement of the illumination color at many locations within multi-illuminant scenes. A practical approach to obtaining such ground-truth illumination data is presented here. The proposed method involves using a drone to carry a gray ball of known percent surface spectral reflectance throughout a scene while photographing it frequently during the flight using a calibrated camera. The captured images are then post-processed. In the post-processing step, machine vision techniques are used to detect the gray ball within each frame. The camera RGB of light reflected from the gray ball provides a measure of the illumination color at that location. In total, the dataset contains 30 scenes with 100 illumination measurements on average per scene. The dataset is available for download free of charge.


2021 ◽  
Author(s):  
Jingchun Zhou ◽  
Tongyu Yang ◽  
Wenqi Ren ◽  
Dan Zhang ◽  
Weishi Zhang

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