Facial Landmark

Facial landmark detection focuses on precisely locating key facial features in images or videos, serving as crucial input for various applications like emotion recognition, gaze estimation, and face recognition. Current research emphasizes improving accuracy and efficiency, particularly for resource-constrained devices, using lightweight models like those based on HRNet architectures and exploring techniques such as knowledge distillation and self-supervised learning. This field is significant due to its broad applicability across diverse domains, including healthcare (e.g., pain assessment, depression detection), human-computer interaction, and security (e.g., anti-spoofing), driving advancements in both fundamental computer vision and practical applications.