Illuminant estimation error detection for outdoor scenes using transformers (CROSBI ID 720666)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Vršnak, Donik ; Domislović, Ilija ; Subašić, Marko ; Lončarić, Sven
engleski
Illuminant estimation error detection for outdoor scenes using transformers
Color constancy is an important property of the human visual system that allows us to recognize the colors of objects regardless of the scene illumination. Computational color constancy is an unavoidable part of all modern camera image processing pipelines. However, most modern computational color constancy methods focus on the estimation of only one illuminant per scene, even though the scene may have multiple illuminations, such as very common outdoor scenes illuminated by sunlight. In this work, we address this problem by creating a deep learning model for image segmentation based on the transformer architecture, which can identify regions in outdoor scenes where the global estimation and subsequent color correction of the image is not accurate. We compare our convolution-free model to a convolutional model and a more simple baseline model and achieve excellent results.
Image segmentation ; Image color analysis ; Convolution ; Computational modeling ; Pipelines ; Lighting ; Computer architecture
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Podaci o prilogu
276-281.
2021.
objavljeno
10.1109/ISPA52656.2021.9552045
Podaci o matičnoj publikaciji
Proceedings of the 12th International Symposium on Image and Signal Processing and Analysis
Zagreb: Institute of Electrical and Electronics Engineers (IEEE)
978-1-6654-2639-8
1845-5921
1849-2266
Podaci o skupu
12th International Symposium on Image and Signal Processing and Analysis (ISPA 2021)
predavanje
13.09.2021-15.09.2021
Zagreb, Hrvatska