SynergyNet is a computer vision research project that leverages deep neural networks to perform 3D face reconstruction and alignment. The model synergistically combines 3D Morphable Models (3DMM) with 3D facial landmarks to achieve state-of-the-art accuracy on facial keypoint detection, head pose estimation, and 3D face mesh generation. Published at 3DV 2021, it provides both full training code and simplified inference APIs for integrating the model into other projects.