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Next Generation Image Style Transfer via CNN
Adar Elad & Mark Erlich
Supervised by Alona Golts
Abstract
Image Style Transfer refers to an artistic process in which a content image is modified to include the style taken from a second image. Early signs of this idea appeared in the early 2000's, but the real breakthrough came with the impressive work of Leon Gatys and his co-authors. Their method relies on pre-learned neural networks, that has been trained for image recognition. Our project focuses on expanding and improving the prime weaknesses of Gatys’ algorithm: (i) preservation of edges; (ii) enabling treatment of large images; and (iii) speeding up the whole transfer process
Pictures
Project Report
Please, see project report.
Final Presentation
Please, see final presentation.