Converting Night-Time Images to Day-Time Images through a Deep Learning Approach

N. Capece, U. Erra, Raffaele Scolamiero
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引用次数: 7

Abstract

This paper examines the application of a deep learning approach to converting night-time images to day-time images. In particular, we show that a convolutional neural network enables the simulation of artificial and ambient light on images. In this paper, we illustrate the design of the deep neural network and some preliminary results on a real indoor environment and two virtual environments rendered with a 3D graphics engine. The experimental results are encouraging and confirm that a convolutional neural network is an interesting approach in the fields of photo-editing and digital image postprocessing.
通过深度学习方法将夜间图像转换为白天图像
本文研究了将夜间图像转换为白天图像的深度学习方法的应用。特别是,我们展示了卷积神经网络能够在图像上模拟人工光和环境光。在本文中,我们举例说明了深度神经网络的设计,并在一个真实的室内环境和两个用三维图形引擎渲染的虚拟环境上取得了一些初步结果。实验结果令人鼓舞,并证实了卷积神经网络在照片编辑和数字图像后处理领域是一种有趣的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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