Multi-view frontal face image generation: A survey

Face images from different perspectives reduce the accuracy of face recognition, and the generation of frontal face images is an important research topic in the field of face recognition. To understand the development of frontal face generation models and grasp the current research hotspots and trends, existing methods based on 3D models, deep learning, and hybrid models are summarized, and the current commonly used face generation methods are introduced. Dataset, and compare the performance of existing models through experiments. The purpose of this paper is to fundamentally understand the advantages of existing frontal face generation, sort out the key issues of such generation, and look toward future development trends.

Automated summary

This article summarizes existing methods for frontal face generation and compares their performance. Through these methods, we can gain a better understanding of the advantages and key issues in frontal face generation, and look towards future development trends.