face-alignment

Face-alignment is the industry-standard implementation of the 'How far are we from solving the 2D & 3D Face Alignment problem?' research, widely regarded as one of the most robust tools for facial landmark detection in the wild. Built on PyTorch, it utilizes a Face Alignment Network (FAN) which employs heatmap regression to identify 68 landmark points with high precision across varying poses and occlusions. By 2026, the tool remains a foundational pillar for both academic research and commercial pipelines in augmented reality, driver monitoring systems (DMS), and deepfake detection. Its architecture is specifically optimized for sub-pixel accuracy and handles extreme head poses that traditional dlib-based methods fail to capture. The 2026 market position sees this tool as the preferred open-source alternative to proprietary APIs like Google ML Kit or Amazon Rekognition, particularly for developers requiring full data sovereignty and offline edge-processing capabilities. It supports multiple detection backends including SFD (S3FD), BlazeFace, and dlib, allowing for a flexible trade-off between inference speed and detection accuracy.