SVAD is a novel method for creating high-quality 3D human avatars from a single image by combining the strengths of video diffusion models and 3D Gaussian Splatting techniques. It generates synthetic training data, enhances identity preservation, and enables real-time rendering, outperforming existing single-image methods in maintaining consistency and detail. Evaluations show SVAD's effectiveness in generating robust avatars from diverse sources while allowing for text-guided editing of avatar attributes.