Virtual reality (VR) offers an artificial, computer generated simulation of a real life environment. It originated in the 1960s and has evolved to provide increasing immersion, interactivity, imagination, and intelligence. Because deep learning systems are able to represent and compose information at various levels in a deep hierarchical fashion, they can build very powerful models which leverage large quantities of visual media data. Intelligence of VR methods and applications has been significantly boosted by the recent developments in deep learning techniques. VR content creation and exploration relates to image and video analysis, synthesis and editing, so deep learning methods such as fully convolutional networks and general adversarial networks are widely employed, designed specifically to handle panoramic images and video and virtual 3D scenes. This article surveys recent research that uses such deep learning methods for VR content creation and exploration. It considers the problems involved, and discusses possible future directions in this active and emerging research area.

中文翻译：

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深度学习的VR内容创建和探索：一项调查

虚拟现实（VR）提供了人工计算机生成的真实生活环境的模拟。它起源于1960年代，并经过发展以提供越来越丰富的沉浸感，互动性，想象力和智力。由于深度学习系统能够以深度分层的方式在各个级别上表示和组合信息，因此它们可以构建利用大量可视媒体数据的功能非常强大的模型。深度学习技术的最新发展极大地促进了VR方法和应用程序的智能化。VR内容的创建和探索涉及图像和视频的分析，合成和编辑，因此广泛使用了深度学习方法，例如全卷积网络和通用对抗网络，专为处理全景图像，视频和虚拟3D场景而设计。本文概述了使用这种深度学习方法进行VR内容创建和探索的最新研究。它考虑了所涉及的问题，并讨论了这个活跃和新兴的研究领域中可能的未来方向。