Inpainting

Inpainting and outpainting are AI image editing techniques for modifying existing images. Inpainting: Fills masked/removed regions with contextually appropriate content. Uses: Remove unwanted objects, repair damaged photos, fill missing regions. Models understand scene context (textures, lighting, perspective) to generate seamless fills. Outpainting: Extends images beyond original borders, generating new content that maintains consistency with existing image. Creates wider scenes, extends portraits to full-body, adds environmental context. Technical approach: Both use diffusion models (Stable Diffusion, DALL-E 2) or GANs trained on paired data. Conditioning on visible pixels while generating masked regions. Tools: Photoshop Generative Fill, Runway ML, ComfyUI, Automatic1111 WebUI with inpaint models. Best practices: Use feathered masks for seamless blending, provide strong visual context around edit regions, iterate with different seeds, combine with manual touch-ups for professional results. Outpainting works best with consistent lighting and clear scene structure.