With the advances of data-driven machine learning research, a wide variety of prediction
problems have been tackled. It has become critical to explore how machine learning and …

Graph Neural Networks (GNNs) have gained momentum in graph representation learning
and boosted the state of the art in a variety of areas, such as data mining (eg, social network …

Perceiving the shape and structure of the real three-dimensional world through sensors and
cameras is indispensable across various domains. The 3D reconstruction technology is …

Deepfake is a technology dedicated to creating highly realistic facial images and videos
under specific conditions, which has significant application potential in fields such as …

In this article, we provide a detailed survey of 3D Morphable Face Models over the 20 years
since they were first proposed. The challenges in building and applying these models …

Graph neural networks provide a powerful toolkit for embedding real-world graphs into low-
dimensional spaces according to specific tasks. Up to now, there have been several surveys …

A large number of intelligent models for masked face recognition (MFR) has been recently
presented and applied in various fields, such as masked face tracking for people safety or …

Recent learning approaches that implicitly represent surface geometry using coordinate-
based neural representations have shown impressive results in the problem of multi-view …

While existing methods for 3D face reconstruction from in-the-wild images excel at
recovering the overall face shape they commonly miss subtle extreme asymmetric or rarely …

With the rapid development of 3D reconstruction, especially the emergence of algorithms
such as NeRF and 3DGS, 3D reconstruction has become a popular research topic in recent …