Replace faces in images and video clips using neural face detection and blending algorithms. Upload source and target media, and our AI maps facial landmarks to generate natural-looking swaps while preserving lighting, angles, and expressions.
At Wireflow, Andrew and the team have built and iterated on 200+ face swap - swap faces in photos and videos with workflows for creative teams and agencies. The approach below reflects what we've found delivers the most consistent, production-ready results.
Capabilities validated across hundreds of production workflows and real client deliverables.
Maps facial geometry using 68 distinct points including jawline, eyebrows, nose bridge, and lip contours. This granular detection enables accurate face alignment even when source and target have different face shapes or proportions, preserving expression details during the swap.
Analyzes skin tone distribution in LAB color space and applies histogram matching to blend the source face naturally with target lighting. Adjusts for warm/cool temperature differences and compensates for shadow density without manual color grading.
Detects and processes up to 8 faces in a single image, allowing selective swapping in group photos or crowd scenes. Click individual faces to choose which to swap, or batch-apply one source face to all detected faces simultaneously.
Download results as PNG files with transparency masks isolating the swapped face region. Useful for compositing workflows in video editors or photo manipulation software where you need layer-based control over the final blend and positioning.
Get started in just a few simple steps.
Select the image containing the face you want to apply (source) and the image or video where you want it to appear (target). For best results, use images where both faces are at least 300x300 pixels and have similar lighting angles.
Set landmark detection sensitivity (high for side angles, standard for frontal), blend strength (0.8 recommended), and edge feathering radius (20px default). Enable color matching to automatically adjust skin tones, or disable for artistic effects.
Process the swap and review the result. If edges appear harsh, increase feathering to 25-30px. If skin tones don't match, adjust color transfer intensity. For video, preview the first 3 seconds before processing the full clip to verify tracking accuracy.
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Start creating instantly with these pre-built AI workflows. Customize them to fit your needs.
AI face swap is a computer vision technique that detects facial landmarks in two images or video frames, then transfers the facial features from a source face onto a target face. The AI maps key points like eyes, nose, mouth, and jawline, then blends skin tones and adjusts lighting to create a natural-looking composite. Modern face swap models use deep learning to preserve expressions and head angles from the target while applying facial structure from the source.
Upload a source image containing the face you want to apply and a target image where you want that face to appear. The AI detects facial landmarks in both images, aligns the geometry using affine transformations, and blends the source face onto the target using color transfer algorithms. You can adjust blend strength (typically 0.7-0.9 works best), feathering radius for edge softness, and color matching intensity to refine the output.
Yes, video face swapping processes each frame individually while maintaining temporal consistency between frames. Upload a video file and a source face image, and the AI tracks the target face across frames using optical flow algorithms. For a 10-second clip at 30fps, this means processing 300 individual swaps with frame-to-frame smoothing to prevent flickering. Video swaps work best with footage under 60 seconds and faces larger than 200x200 pixels.
Unnatural results typically occur when lighting direction differs by more than 30 degrees between source and target, when face angles exceed 45-degree rotation, or when skin tone variance is too high for the color transfer algorithm to compensate. Using source and target images with similar lighting conditions, frontal or near-frontal angles, and matching image resolution (both above 512px) produces the most convincing swaps. Edge feathering between 15-25 pixels also prevents harsh cutoff lines.
JPG and PNG files with faces at least 256x256 pixels produce reliable landmark detection. Higher resolution sources (1024px or larger) allow for better detail preservation when swapping onto high-resolution targets. The AI performs color space conversion to LAB for better skin tone matching, so images with accurate white balance yield more natural results. For video, MP4 and MOV formats at 1080p resolution with H.264 encoding provide the best balance of quality and processing time.
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Try free →Written by
Andrew AdamsCo-Founder & Operations at Wireflow
Runs client operations and content strategy at Wireflow. Works directly with creative teams and agencies to build production AI workflows.
Upload your source and target images to generate face swaps with automatic landmark detection and color matching
Replace faces in images and video clips using neural face detection and blending algorithms. Upload source and target media, and our AI maps facial landmarks to generate natural-looking swaps while preserving lighting, angles, and expressions.
At Wireflow, Andrew and the team have built and iterated on 200+ face swap - swap faces in photos and videos with workflows for creative teams and agencies. The approach below reflects what we've found delivers the most consistent, production-ready results.
Capabilities validated across hundreds of production workflows and real client deliverables.
Maps facial geometry using 68 distinct points including jawline, eyebrows, nose bridge, and lip contours. This granular detection enables accurate face alignment even when source and target have different face shapes or proportions, preserving expression details during the swap.
Analyzes skin tone distribution in LAB color space and applies histogram matching to blend the source face naturally with target lighting. Adjusts for warm/cool temperature differences and compensates for shadow density without manual color grading.
Detects and processes up to 8 faces in a single image, allowing selective swapping in group photos or crowd scenes. Click individual faces to choose which to swap, or batch-apply one source face to all detected faces simultaneously.
Download results as PNG files with transparency masks isolating the swapped face region. Useful for compositing workflows in video editors or photo manipulation software where you need layer-based control over the final blend and positioning.
Get started in just a few simple steps.
Select the image containing the face you want to apply (source) and the image or video where you want it to appear (target). For best results, use images where both faces are at least 300x300 pixels and have similar lighting angles.
Set landmark detection sensitivity (high for side angles, standard for frontal), blend strength (0.8 recommended), and edge feathering radius (20px default). Enable color matching to automatically adjust skin tones, or disable for artistic effects.
Process the swap and review the result. If edges appear harsh, increase feathering to 25-30px. If skin tones don't match, adjust color transfer intensity. For video, preview the first 3 seconds before processing the full clip to verify tracking accuracy.
Build Any AI Workflow
AI Models Integrated
Full Commercial License
Start creating instantly with these pre-built AI workflows. Customize them to fit your needs.
AI face swap is a computer vision technique that detects facial landmarks in two images or video frames, then transfers the facial features from a source face onto a target face. The AI maps key points like eyes, nose, mouth, and jawline, then blends skin tones and adjusts lighting to create a natural-looking composite. Modern face swap models use deep learning to preserve expressions and head angles from the target while applying facial structure from the source.
Upload a source image containing the face you want to apply and a target image where you want that face to appear. The AI detects facial landmarks in both images, aligns the geometry using affine transformations, and blends the source face onto the target using color transfer algorithms. You can adjust blend strength (typically 0.7-0.9 works best), feathering radius for edge softness, and color matching intensity to refine the output.
Yes, video face swapping processes each frame individually while maintaining temporal consistency between frames. Upload a video file and a source face image, and the AI tracks the target face across frames using optical flow algorithms. For a 10-second clip at 30fps, this means processing 300 individual swaps with frame-to-frame smoothing to prevent flickering. Video swaps work best with footage under 60 seconds and faces larger than 200x200 pixels.
Unnatural results typically occur when lighting direction differs by more than 30 degrees between source and target, when face angles exceed 45-degree rotation, or when skin tone variance is too high for the color transfer algorithm to compensate. Using source and target images with similar lighting conditions, frontal or near-frontal angles, and matching image resolution (both above 512px) produces the most convincing swaps. Edge feathering between 15-25 pixels also prevents harsh cutoff lines.
JPG and PNG files with faces at least 256x256 pixels produce reliable landmark detection. Higher resolution sources (1024px or larger) allow for better detail preservation when swapping onto high-resolution targets. The AI performs color space conversion to LAB for better skin tone matching, so images with accurate white balance yield more natural results. For video, MP4 and MOV formats at 1080p resolution with H.264 encoding provide the best balance of quality and processing time.
Explore our collection of AI-powered creative tools. Each tool is free to try with no watermarks.
Generate vertical format videos optimized for mobile platforms using AI. Automatically format horizontal content to 9:16 aspect ratio, add captions, apply platform-specific templates, and export in multiple resolutions for TikTok, Instagram Reels, and YouTube Shorts.
Try free →Convert written narratives into multi-scene video stories with automated visual sequencing, character consistency across frames, and synchronized narration. Built for content creators producing educational series, brand narratives, and social media story content at scale.
Try free →Generate original images from text prompts using neural networks trained on millions of visual concepts. Control composition, style, lighting, and subject matter through natural language descriptions without manual drawing or photo editing skills.
Try free →Generate custom digital artwork in styles ranging from photorealism to anime using text-based prompts. Control composition, color palettes, and artistic techniques without traditional drawing skills.
Try free →Convert written scripts, articles, and text descriptions into video content with synchronized visuals, voiceover, and scene transitions. Our AI analyzes narrative structure to generate contextually relevant video sequences that match your script's pacing and tone.
Try free →Generate video content from text prompts, scripts, or storyboards using multi-modal AI models. Wireflow combines text-to-video synthesis with automated scene composition, motion control, and audio synchronization to produce broadcast-ready footage without camera equipment or editing software.
Try free →Written by
Andrew AdamsCo-Founder & Operations at Wireflow
Runs client operations and content strategy at Wireflow. Works directly with creative teams and agencies to build production AI workflows.
Upload your source and target images to generate face swaps with automatic landmark detection and color matching
