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Recurrent Color Constancy

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Details

Original languageEnglish
Title of host publication2017 IEEE International Conference on Computer Vision (ICCV)
PublisherIEEE
ISBN (Electronic)978-1-5386-1032-9
DOIs
Publication statusPublished - 2017
Publication typeA4 Article in a conference publication
EventIEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION -
Duration: 1 Jan 1900 → …

Publication series

Name
ISSN (Electronic)2380-7504

Conference

ConferenceIEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION
Period1/01/00 → …

Abstract

We introduce a novel formulation of temporal color constancy which considers multiple frames preceding the frame for which illumination is estimated. We propose an end-to-end trainable recurrent color constancy network – the RCC-Net – which exploits convolutional LSTMs and a simulated sequence to learn compositional representations in space and time. We use a standard single frame color constancy benchmark, the SFU Gray Ball Dataset, which can be adapted to a temporal setting. Extensive experiments show that the proposed method consistently outperforms single-frame state-of-the-art methods and their temporal variants.

Publication forum classification

Field of science, Statistics Finland