Best 3 AI Image Restoration Tools of 2025

FLUX.1-dev-Controlnet-Inpainting-Alpha is an AI image restoration model released by the AlimamaCreative Team, specifically developed to repair and fill in missing or damaged areas of images. This model performs optimally at a resolution of 768x768, delivering high-quality image restoration. As an alpha version, it showcases advanced technology in the field of image restoration and is expected to provide even better performance with further training and optimization.

SUPIR is a groundbreaking image repair method utilizing the power of generative priors and model expansion. Through multi-modal techniques and advanced generative priors, SUPIR has made significant strides in intelligent and realistic image repair. Model expansion, a key catalyst within SUPIR, has significantly enhanced its capabilities, revealing new potential in image repair. We trained our model on a dataset of 20 million high-resolution, high-quality images, each accompanied by descriptive textual annotations. SUPIR can repair images based on text prompts, broadening its application range and potential. Furthermore, we introduced negative quality prompts to further improve perceived quality. We also developed a repair-guided sampling method to mitigate the fidelity issues encountered in generative repair. Experiments have demonstrated SUPIR's outstanding repair effects and its novel ability to manipulate repairs through text prompts.

DiffBIR is a blind image recovery model based on generative diffusion prior. It removes image degradation through two-stage processing and refines image details. DiffBIR's advantages lie in providing high-quality image recovery results and having flexible parameter settings, allowing for a balance between fidelity and quality. The model is free to use.