Exploring 3D-aware Lifespan Face Aging via Disentangled Shape-Texture
  Representations
Qianrui Teng Rui Wang Xing Cui Peipei Li Zhaofeng He
Existing face aging methods often focus on modeling either texture aging or
using an entangled shape-texture representation to achieve face aging. However,
shape and texture are two distinct factors that mutually affect the human face
aging process. In this paper, we propose 3D-STD, a novel 3D-aware Shape-Texture
Disentangled face aging network that explicitly disentangles the facial image
into shape and texture representations using 3D face reconstruction.
Additionally, to facilitate high-fidelity texture synthesis, we propose a novel
texture generation method based on Empirical Mode Decomposition (EMD).
Extensive qualitative and quantitative experiments show that our method
achieves state-of-the-art performance in terms of shape and texture
transformation. Moreover, our method supports producing plausible 3D face aging
results, which is rarely accomplished by current methods.