AI Background Remover

An AI background remover takes a photo and separates the main subject from everything behind it. This tool runs a U²-Net segmentation model compiled to WebAssembly, which analyzes the image pixel by pixel and predicts a mask marking where the subject ends and the background begins. It then erases the background and returns a clean cutout with the subject's edges preserved.

Because the model does semantic segmentation rather than simple color keying, it handles subjects sitting against busy or similarly colored backgrounds, with no green screen or manual selection needed.

Reach for it when you need a product shot on a plain white or transparent field, a portrait to drop into a new scene, or a logo-style cutout for a slide, a thumbnail, or a marketplace listing. Swapping the background for a solid brand color is the fastest way to standardize a set of product photos.

It also helps when you want a transparent PNG to layer inside a design tool, or a composite where your subject appears in front of a completely different photo.

Drop in a JPG of a person standing in front of a cluttered room. The model isolates the person, and the result panel shows them over a checkerboard that signals transparency. Pick 'Solid Color' and choose white, and the background fills instantly; or pick 'Image' and upload a beach photo to composite the person onto it. Export as PNG to keep the transparent edges, or as JPG to flatten the cutout against the chosen background into a smaller file.

The first run downloads the ~4.4MB model once and caches it, so later removals start immediately. Results are strongest when the subject stands out clearly from the backdrop: high-contrast images with well-defined edges give the cleanest masks, while wispy hair or transparent objects like glass are the hardest cases for any segmentation model. Inputs can be JPG, PNG, or WebP up to 10MB. Transparency only survives in the PNG export, since a JPG has no alpha channel and always bakes in whichever background you selected.