MotionFollower is a lightweight score-guided diffusion model designed for video motion editing. It utilizes two lightweight signal controllers to separately control pose and appearance, avoiding heavy attention computations. The model employs a dual-branch architectural design based on the score-guided principle, including reconstruction and editing branches, significantly enhancing its ability to model texture details and complex backgrounds. Experiments demonstrate that MotionFollower reduces GPU memory usage by approximately 80% compared to the state-of-the-art motion editing model MotionEditor, while providing superior motion editing performance. It also exclusively supports extensive camera movement and complex actions.