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	Author	Marco Buzzelli; Joost Van de Weijer; Raimondo Schettini
	Title	Learning Illuminant Estimation from Object Recognition			Type	Conference Article
	Year	2018	Publication	25th International Conference on Image Processing	Abbreviated Journal
	Volume		Issue		Pages	3234 - 3238
	Keywords	Illuminant estimation; computational color constancy; semi-supervised learning; deep learning; convolutional neural networks
	Abstract	In this paper we present a deep learning method to estimate the illuminant of an image. Our model is not trained with illuminant annotations, but with the objective of improving performance on an auxiliary task such as object recognition. To the best of our knowledge, this is the first example of a deep learning architecture for illuminant estimation that is trained without ground truth illuminants. We evaluate our solution on standard datasets for color constancy, and compare it with state of the art methods. Our proposal is shown to outperform most deep learning methods in a cross-dataset evaluation setup, and to present competitive results in a comparison with parametric solutions.
	Address	Athens; Greece; October 2018
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference	ICIP
	Notes	LAMP; 600.109; 600.120			Approved	no
	Call Number	Admin @ si @ BWS2018			Serial	3157
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