Facial Wrinkle

Facial wrinkle research focuses on accurately detecting and manipulating wrinkles in images, driven by applications in cosmetic dermatology, biometric verification, and robotic manipulation of fabrics. Current research employs convolutional neural networks (CNNs) for wrinkle segmentation, often leveraging techniques like transfer learning and weak supervision to improve accuracy and efficiency, and incorporating novel loss functions to enhance realism in wrinkle removal. These advancements are improving automated analysis of wrinkles for diagnostic and aesthetic purposes, as well as enabling more sophisticated image processing and robotic control.