Face Alignment

Face alignment, the process of precisely locating facial features in images or videos, is crucial for various applications like facial recognition, expression analysis, and 3D face modeling. Current research emphasizes improving robustness to low-quality inputs, misalignments, and partial data, often employing deep learning architectures such as convolutional neural networks (CNNs), transformers, and graph convolutional networks (GCNs), sometimes combined with techniques like knowledge distillation and neural architecture search. These advancements enhance accuracy and efficiency, leading to improved performance in applications ranging from biometric authentication to clinical diagnostics and animation. The development of large, diverse datasets and novel loss functions further contributes to the field's progress.