论文标题
Deep-VFX：简短视频的深度动作识别驱动的VFX
Deep-VFX: Deep Action Recognition Driven VFX for Short Video
论文作者
论文摘要
人类运动是传达信息的关键功能。在应用程序中，短形式移动视频在世界各地都非常受欢迎，例如Tik Tok。用户想添加更多的VFX，以追求创造力和个人。短视频平台上添加了许多特殊效果。这些使用户更有可能炫耀这些个性。常见和传统的方式是创建VFX的模板。但是，为了综合完美，用户必须尝试掌握新模板的时机和节奏。它不容易使用，尤其是对于移动应用程序。本文旨在通过运动驱动而不是传统模板匹配来改变VFX综合。我们提出了改善此VFX合成的AI方法。详细说明，为了增加对人体的特殊影响。在该系统中，骨骼提取至关重要。我们还提出了一种新颖的LSTM形式，以通过行动识别来找出用户的意图。该实验表明，我们的系统使VFX能够更轻松，更有效地生成VFX。
Human motion is a key function to communicate information. In the application, short-form mobile video is so popular all over the world such as Tik Tok. The users would like to add more VFX so as to pursue creativity and personlity. Many special effects are added on the short video platform. These gives the users more possibility to show off these personality. The common and traditional way is to create the template of VFX. However, in order to synthesis the perfect, the users have to tedious attempt to grasp the timing and rhythm of new templates. It is not easy-to-use especially for the mobile app. This paper aims to change the VFX synthesis by motion driven instead of the traditional template matching. We propose the AI method to improve this VFX synthesis. In detail, in order to add the special effect on the human body. The skeleton extraction is essential in this system. We also propose a novel form of LSTM to find out the user's intention by action recognition. The experiment shows that our system enables to generate VFX for short video more easier and efficient.
