MOFA-Video is a method that animates single images using various control signals. It employs sparse-to-dense (S2D) motion generation and flow-based motion adaptation techniques, effectively utilizing different types of control signals such as trajectories, keypoint sequences, and their combinations to animate single images. During training, sparse control signals are generated through sparse motion sampling, and different MOFA-Adapters are trained to animate videos using pre-trained SVDs. In inference, different MOFA-Adapters can be combined to jointly control frozen SVDs.