AI People Remover removes distracting people from a photo you have the right to edit and reconstructs the background they covered. Upload one image, identify the bystander or group, and generate a cleaner scene while keeping the intended subject, remaining people and composition recognizable.
Describe who should be removed and who must remain. That distinction is important in travel, event and street photographs where several people appear at different depths and a vague instruction could erase the intended subject or alter a face.
Try it nowA removed person may cover pavement, furniture, landscape or architectural detail. The model generates a plausible continuation from surrounding context, including perspective, light and texture, instead of leaving a cutout or simply smearing nearby pixels across the gap.
Try it nowThe system prompt asks the model to keep all remaining people and their identities stable along with foreground objects, color and framing. This boundary reduces unrelated edits, although every generated result should still be checked closely before publication.
Try it nowPeople removal changes the record represented by an image. APIXO positions this workflow for content you own or are authorized to modify, not for deceptive documentary alteration, impersonation or editing private images without permission from the relevant rights holder.
Try it nowRemove an incidental background visitor while retaining the traveler, landmark, weather, light and original point of view.
Clear authorized listing photographs of passersby while keeping rooms, streets, boundaries and permanent property details honest.
Create an alternate crop-like composition by removing an unrelated bystander from an image you may edit and share.
Remove an accidental person in the background while keeping the product, styling and intentional talent unchanged.
Prepare a less crowded source before using Background Changer or Blur Background for a separate creative treatment.
Test a lawful cleanup instruction in the workbench, then use the corresponding model API for approved asset pipelines.
Clean authorized personal photographs when an incidental bystander distracts from the intended person or place.
Prepare owned interior or exterior images while preserving permanent features and avoiding misleading structural changes.
Create approved promotional variants from commissioned photography when distracting attendees appear outside the main action.
Simplify licensed scenes before a background, lighting or campaign treatment is developed for a client asset.
GPT-Image-2.5OpenAIGPT-Image-2OpenAI
Seedream 5.0 ProByteDanceSeedream 5.0ByteDanceSeedream 4.5ByteDance
Nano Banana ProGoogleNano Banana 2GoogleNano BananaGoogle
Qwen Image 3.0 ProAlibabaQwen Image 3.0Alibaba
Flux 2Black Forest LabsFlux KontextBlack Forest Labs
MidjourneyMidjourney
MiniMax Image 01MiniMaxWan 2.6 ImageAlibabaWan 2.5 ImageAlibaba
Grok ImagexAIChoose an authorized photo with a clear intended subject and visible context around the person to remove.
Describe the bystander or group by position and clothing, and state which people and identities must stay unchanged.
Inspect reconstructed edges, remaining faces, shadows and reflections before downloading or refining the instruction.
Identify the person by clothing, position and depth, then state clearly which people must remain.
Use images with enough visible background around the person to guide reconstruction of hidden surfaces.
Inspect hands, faces, reflections and overlapping bodies because those boundaries are difficult to reconstruct reliably.
Avoid presenting generated cleanup as an unchanged documentary record when the removed person affects the meaning.
Only process images you own or have permission to edit, publish and use for the intended purpose.
AI People Remover is a prompt-guided image editor that removes a described person or group and generates a plausible version of the background they obscured. It operates on one uploaded image without a separate mask, so the description must distinguish people to remove from people to retain.
Describe both sides of the boundary. Identify the unwanted person by location, clothing or role, then identify the main subject and details that must remain. After generation, check faces, limbs and overlaps carefully because a single image does not reveal what was hidden behind them.
Use it only for images you own or have permission to edit and for lawful purposes consistent with the rights of pictured people and other rights holders. Do not use generated edits to deceive, harass, impersonate or misrepresent an image as an unchanged factual record.
Use a clear image accepted by the upload control. A well-lit source with visible edges and enough surrounding context gives the model more information to preserve important details. Very small, heavily compressed, blocked or ambiguous areas can make reconstruction and fine lettering less consistent.
Generation uses credits based on the model and parameters selected for the task. The workbench shows an estimate before submission, so you can review the expected charge before starting. Switching models or output settings can change that estimate without changing the purpose of the tool.
Yes. The models that power the workbench are also available through APIXO APIs for developers building repeatable image workflows. The related model pages explain current request fields and response handling. Use the workbench for visual testing, then choose the matching model documentation for integration.
Commercial use depends on your rights to the source image, its people, logos, artwork and other protected material, together with the terms that apply to your selected model and destination. Only upload content you are authorized to edit, and review relevant permissions before publishing or selling the result.
Upload a photo you are allowed to edit, point out the distracting person, and let the scene be rebuilt around your intended subject.
Try it now
