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Image Colorization with Deep Convolutional Neural …

Image Colorization with deep Convolutional Neural NetworksJeff present a Convolutional - Neural - network -based sys-tem that faithfully colorizes black and white photographicimages without direct human assistance. We explore var-ious network architectures, objectives, color spaces, andproblem formulations. The final classification-based modelwe build generates colorized images that are significantlymore aesthetically-pleasing than those created by the base-line regression-based model, demonstrating the viability ofour methodology and revealing promising avenues for fu-ture IntroductionAutomated Colorization of black and white images hasbeen subject to much research within the computer visionand machine learning communities. Beyond simply beingfascinating from an aesthetics and artificial intelligence per-spective, such capability has broad practical applicationsranging from video restoration to Image enhancement forimproved , we take a statistical-learning-driven approach to-wards solving this problem.

has become standard for convolutional neural networks. Figure 2. Regression network schematic. One downside of using the rectified linear unit as the ac-tivation function in a neural network is that the model pa-rameters can be updated in such a way that the function’s active region is always in the zero-gradient section. In this

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