Cambio de rostros en video múltiple

Detecta rostros en un video y asigna cada persona a un retrato de reemplazo.

Video original

Sube primero el video de origen y luego detecta las pistas faciales representativas.

Costo estimado

No se pudo leer la duración

Duración del video

What is Multi Video Face Swap?

Multi Video Face Swap is an AI video tool for replacing selected faces in a source clip after detecting visible face tracks, so each person can be mapped to the right replacement portrait.

Start with one source video

Upload the clip that should keep its camera movement, body motion, outfits, background, timing, and scene context. The video remains the base for the generated result.

Map faces before generation

Run face detection first, then review the detected face cards. You can apply one replacement portrait to all detected faces or upload a different portrait for each person you want to change.

Review every replaced face before sharing

Multi-person video edits are identity-sensitive. Use only videos and portraits you have rights to use, check the full clip for artifacts, and avoid impersonation or misleading contexts.

Example: replace two faces in one video

This page-specific demo shows the input and output logic for multi-person video face swap. The source video provides motion, hair, outfits, body movement, camera framing, and scene context; the replacement portraits provide only the new face identities.

Source video	Replacement faces	Output video
The source clip keeps the vintage studio, camera framing, motion, hair, outfits, body pose, and lighting.	Each portrait is mapped to one detected person in the video and supplies only the face identity.	The output keeps the source hair, outfits, body motion, and cinematic studio scene while replacing each person's face with the mapped portrait.

How does multiple face mapping work in a video?

The workflow separates detection from generation so you can confirm which people appear in the clip before assigning replacement portraits.

Stage	What PopcornAI does	What you decide
Source video	The uploaded video provides the final clip's motion, body position, camera framing, outfits, background, lighting changes, and timing.	Choose a clip where the faces you want to replace are visible for enough of the video to inspect.
Face detection	PopcornAI detects representative visible faces from the video and returns face cards in the workspace.	Confirm each detected face card before uploading replacement portraits, especially when people look similar or cross paths.
Replacement mapping	Each detected face can receive its own portrait, or one uploaded portrait can be applied to all detected faces when that is the intended result.	Upload clear portraits only for the people you want to change. Leave unwanted detections unmapped.
Final clip review	The generated video keeps the source clip as the base while replacing the mapped faces across the video.	Watch the full output, check face continuity, and confirm you have consent before publishing or sending the clip.

When should you use multi-person video face swap?

Use this workflow when the hard part is controlling which person in a video receives which replacement face.

Task	Why this tool fits	Check before generating
Group clip edits	Replace one or more people in a party clip, team video, group performance, or staged scene while preserving the original motion and background.	Fast movement, motion blur, tiny faces, heavy occlusion, or people turning away can make detection and blending weaker.
Cast and character previews	Preview different faces in the same moving scene without rebuilding the video, camera work, outfit, or body movement.	Replacement portraits should match the source video's face angle, lighting direction, and expression range as closely as possible.
Replace only one person in a crowded clip	Face cards make it easier to avoid changing the wrong person when the source video contains several visible faces.	Review the detected cards carefully before mapping, because similar people or brief appearances can be easy to mix up.
Private social or internal drafts	Create consent-based tests, private jokes, storyboard drafts, or internal visual mockups where everyone represented understands the edit.	Do not present the output as real footage or use someone else's likeness without permission.

Workflow

How to swap multiple faces in a video

The workspace uses a detect-then-map flow: upload the video, detect visible faces, assign replacement portraits, then generate and review the final clip.

1. Upload the source video

Choose the clip that should keep its movement, framing, clothing, background, lighting, and timing.

2. Detect visible faces

Run detection so the workspace can show face cards for the people it finds in the video.

3. Upload replacement portraits

Assign a clear face image to each detected person you want to replace, or apply one portrait to all faces when that is intentional.

4. Generate and review

Create the task, then watch the full output in your history panel before downloading or sharing.

Best inputs for natural multi-face video swaps

Video face swap quality depends on both the source clip and every replacement portrait. Check the moving face, not just a single frame.

Input	Works best	Avoid
Source video	Medium or close framing, visible facial landmarks, steady lighting, moderate movement, and enough resolution to inspect each target face.	Very distant crowds, heavy compression, fast cuts, strong motion blur, faces hidden by hands or hair, harsh shadows, or faces cropped by the frame.
Detected face cards	Each card clearly corresponds to a person you can recognize in the clip, with no confusing duplicate or unwanted mappings.	Generating before checking the cards, especially when people pass each other, turn sideways, or appear for only a few frames.
Replacement portraits	One clear face per image, open eyes, natural expression, similar head angle, and lighting close to the source video.	Screenshots, masks, sunglasses, heavy filters, low-resolution crops, group portraits, extreme expressions, or a very different camera angle.
Final review	Watch the full clip for face continuity, lip and eye alignment, skin tone, edge artifacts, and whether the edited context is acceptable.	Checking only the first frame, skipping consent review, or sharing a result that could be mistaken for real footage.

How to fix weak multi-video face swap results

When the output looks wrong, isolate whether the issue came from detection, mapping, source video quality, or a replacement portrait.

Problem	Likely cause	Try this next
A person you need is not detected	The face may be too small, blurred, covered, turned away, cut off by the frame, or visible for too short a time.	Use a clearer clip or trim to a segment where the target person is closer, brighter, and more front-facing.
The wrong person changes	A replacement portrait was assigned to the wrong detected face card, or similar-looking people were mixed up.	Clear the mapping, compare the detected face cards again, and upload the portrait only to the intended person.
One replaced face flickers or drifts	That person may move quickly, rotate their head, pass behind objects, or have lighting changes across the clip.	Try a shorter clip with steadier face visibility, or choose a replacement portrait with a closer angle and lighting direction.
The whole clip looks soft or unstable	The source video may be low resolution, heavily compressed, too long for a first test, or filmed in unstable light.	Test with a shorter, clearer segment first, then process a longer version after the face mapping and portrait quality look correct.

Limits, consent, and when to choose another tool

Multi Video Face Swap is for mapping selected faces in a source video. It is not a way to impersonate people, hide identity, or redesign the entire scene.

Situation	Better choice	Why
The video has one clear main person	Single Video Face Swap	A single-person workflow is simpler when you only need one source video and one replacement portrait.
The source media is a still group photo	Multi Image Face Swap	Static images do not need cross-frame video detection or video duration-based generation.
You want to change clothes, background, style, or camera motion	Video generation or video editing workflows	Face swap keeps the source video as the base. It is not meant to rebuild the full scene.
You do not have permission to use a person's likeness	Do not generate or share the face swap	Use face swap only with appropriate rights and consent. Do not create impersonation, harassment, or misleading sensitive content.

Multi Video Face Swap FAQ

Common questions about using PopcornAI to replace selected faces in a video.

Can I use Multi Video Face Swap before signing in?

You can read the guide and prepare your video and portraits before signing in. Running face detection or generating the final video requires signing in so PopcornAI can manage uploads, credits, and generation history.

What is the difference between single video and multi video face swap?

Single Video Face Swap is for one main person in a clip. Multi Video Face Swap detects multiple visible faces first, then lets you choose which person receives which replacement portrait.

Do I have to replace every detected face?

No. Upload replacement portraits only for the people you want to change. Face cards without a mapped replacement portrait do not need to be part of your intended face map.

Can I apply one face image to all detected people?

Yes. After detection, the workspace includes an apply-one-to-all option. Use it only when every detected face should receive the same replacement portrait.

What files can I upload?

Use one source video and image files for replacement portraits. The current video uploader supports a single video up to 200MB, and the image uploader supports images up to 20MB.

How many credits does a multi video face swap use?

The workspace shows the estimated credits after the video duration is available and before generation. For longer clips, test a short segment first so you can check detection and portrait quality.

Why are some faces not detected?

Faces may be missed when they are small, blurred, side-facing, covered, clipped by the frame, poorly lit, or visible for only a short part of the video. Try a clearer or shorter segment.

Why does one replaced face look worse than the others?

That face may move faster, be more occluded, or have a replacement portrait that does not match the source angle or lighting. Replace that portrait first, then try a clearer clip if the issue remains.

Can I use celebrity photos or someone else's portrait?

Only use videos, images, and likenesses you have the right to use. Do not create swaps that impersonate someone, mislead viewers, or place a real person into a sensitive context without consent.

What should I check before sharing the final video?

Confirm consent and usage rights, watch the full clip for artifacts or wrong mappings, and avoid presenting the edited result as real footage of someone in a misleading situation.