A fast and efficient approach to human animation generation via frame difference

Generating Three-Dimensional Animation of Virtual Characters Based on Monocular RGB Video represents a cutting-edge technological application in the field of computer graphics. Initially, monocular video serves as input data, from which the three-dimensional coordinate information of characters is extracted. Subsequently, this data is mapped onto any three-dimensional character model, enabling the generation of three-dimensional animation corresponding to any character action portrayed in the video. This paper aims to generate three-dimensional animation of virtual characters, leveraging frame interpolation and deep learning methods for implementation. The innovation of this paper primarily lies in the extraction of key frames from the video using frame interpolation. Furthermore, interstitial frame character action data between each key frame is predicted and generated through a neural network model. The resulting three-dimensional animation of characters demonstrates high quality and smoothness.