P‐2.3: Development Prospects and Current Status of Deep Learning Neural Network‐based Facial Capture in the Metaverse Field

The intricate physiological composition of the human face facilitates the manifestation of diverse facial expressions, serving as a conduit for the conveyance of emotions, cognitive states, and the anticipation of future reactions. This multifaceted ability holds paramount significance in character representation. The realistic reconstruction of 3D human facial expressions stands as a focal point within the realms of computer graphics and computer vision research. The endeavor to capture and reconstruct three‐dimensional models depicting facial expressions finds extensive utility across various domains, notably making notable strides in computer games, cinematic productions, medical applications, and social interaction paradigms. This paper directs its attention to the realm of facial animation capture, elucidating the evolution of its manifold techniques and their applications. Furthermore, a meticulous analysis of the distinctions between these techniques ensues, unraveling their respective merits and demerits.