Inpainting is an AI technique that fills in or replaces selected regions of an image with new content that blends seamlessly with the surrounding area. It allows precise, localized editing where specific parts of an image can be removed, modified, or replaced while keeping the rest of the image intact.

The user masks the area to be modified, and the AI analyzes the surrounding context to generate fill content that matches lighting, perspective, style, and subject matter. Inpainting can be guided by text prompts to specify what should appear in the masked region, or it can work without prompts to intelligently continue patterns and content from the surrounding area. The technique is essential for removing unwanted objects, fixing composition problems, replacing elements with alternatives, or adding new subjects to existing scenes.

Inpainting has become a core feature in AI-assisted image editing workflows, integrated into professional tools and specialized AI platforms. It provides surgical precision for targeted edits without requiring regeneration of entire images, making it invaluable for refinement, correction, and creative iteration on both AI-generated and photographed imagery.