CodeFormer is a Transformer-based prediction network for image decimation recovery. By learning discrete codebooks and decoders, it reduces the uncertainty of recovery mapping and generates high-quality faces. It exhibits excellent robustness against degradation and is applicable to both synthetic and real datasets.