Colorization of B/W images & videos using convolutional neural networks (CNN)

dc.contributor.authorTamboli, Mujib
dc.contributor.authorGori, Shakeel (16ET15)
dc.contributor.authorKagdi, Arbaz Altaf (16ET17)
dc.contributor.authorShaikh, Touhid Alam (16ET29)
dc.contributor.authorSharma, Nikhil (16ET30)
dc.date.accessioned2021-11-09T06:43:31Z
dc.date.available2021-11-09T06:43:31Z
dc.date.issued2020-05
dc.description.abstractThe proposed approach present a novel technique to automatically colorize grayscale images that combines both global priors and local image features. Based on Convolutional Neural Networks, our deep network features a fusion layer that allows us to elegantly merge local information dependent on small image patches with global priors computed using the entire image. The entire framework, including the global and local priors as well as the colorization model, is trained in an end-to-end fashion. Furthermore, our architecture can process images of any resolution, unlike most existing approaches based on CNN. We leverage an existing large-scale scene classification database to train our model, exploiting the class labels of the dataset to more efficiently and discriminatively learn the global priors. We validate our approach with a user study and compare against the state of the art, where we show significant improvements. Furthermore, we demonstrate our method extensively on many different types of images, including black-and-white photography from over a hundred years ago, and show realistic colorization. The final classification-based model we build generates colorized images that are significantly more aesthetically-pleasing than those created by the baseline regression-based model, demonstrating the viability of our methodology and revealing promising avenues for future work.en_US
dc.identifier.urihttp://localhost:8080/xmlui/handle/123456789/3625
dc.language.isoenen_US
dc.publisherAIKTCen_US
dc.subjectProject Report - EXTCen_US
dc.titleColorization of B/W images & videos using convolutional neural networks (CNN)en_US
dc.typeOtheren_US
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