增强现实的深度学习

Jean-François Lalonde
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引用次数: 13

摘要

增强现实旨在将真实世界的视觉内容与虚拟对象混合在一起。实现逼真的结果涉及解决具有挑战性的计算机视觉任务,例如跟踪真实的3D物体和估计场景的照明条件。在这篇短文中,我们介绍了如何通过深度学习稳健而准确地解决这两个具有挑战性的任务。在这两种情况下,深度卷积神经网络都是在大量数据上进行训练的,并获得了最先进的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Deep Learning for Augmented Reality
Augmented reality aims to mix real-world visual content with virtual objects. Achieving realistic results involves solving challenging computer vision tasks, such as tracking real 3D objects and estimating the illumination conditions of a scene. In this short paper, we present how these two challenging tasks can be solved robustly and accurately with deep learning. In both cases, deep convolutional neural networks are trained on large amounts of data, and achieve state-of-the-art results.
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