Face Detector

Face detection, the task of automatically locating human faces in images and videos, is a crucial component of many computer vision applications. Current research focuses on improving accuracy and efficiency across diverse conditions, including occlusions (like masks), variations in pose and lighting, and the detection of AI-generated faces, often employing deep learning architectures such as YOLO and variations of ResNet, along with novel loss functions and attention mechanisms. These advancements address biases in existing models and improve robustness against adversarial attacks, impacting fields ranging from security and surveillance to accessibility and healthcare. The development of large, diverse, and demographically annotated datasets is also a key area of focus to mitigate biases and improve fairness.