Background Remover
AI-powered background removal — 100% free, 100% private
Drop images here or click to browse (up to 10)
JPEG, PNG, WebP, AVIF up to 50MB each
How It Works
Drop Your Image
Drag and drop up to 10 images, paste from clipboard, or click to browse. JPEG, PNG, WebP, AVIF up to 50MB each.
AI Removes the Background
A state-of-the-art AI model runs directly in your browser to precisely separate the foreground from the background.
Download Transparent PNG
Get your image with a transparent background as PNG. Optionally add a solid color background before downloading.
How AI Background Removal Works
Semantic Segmentation with Neural Networks
Background removal relies on semantic segmentation — a computer vision task where every pixel in an image is classified as either foreground or background. Modern models like RMBG-1.4 use deep neural networks trained on millions of annotated images to understand which objects are "subjects" (people, products, animals) and which are background. Unlike simple color-based selection (like a green screen), AI segmentation understands object boundaries, handles complex edges like hair and fur, and works with any background color or pattern.
Running AI Models in the Browser
Traditionally, AI inference requires a powerful server with a GPU. Krunkit runs the segmentation model directly in your browser using ONNX Runtime with WebGPU acceleration (falling back to WebAssembly on devices without GPU support). The model (~44MB) downloads once and is cached by your browser for instant future use. This approach means zero server costs, zero data privacy concerns, and the ability to process images offline after the initial model download. Processing time depends on your device — modern laptops handle most images in 2-5 seconds.
Edge Quality and Alpha Matting
The biggest challenge in background removal is handling semi-transparent edges — hair strands, glass objects, soft shadows. Simple binary masks (pixel is either foreground or background) create harsh cutouts. Advanced models produce soft alpha mattes where edge pixels have partial transparency values between 0 and 1, creating natural-looking transitions. Krunkit's model generates these soft edges automatically, preserving the subtle translucency around hair, feathers, and other fine details that would look artificial with hard cuts.
Best Practices for Clean Results
While AI background removal works well on most images, result quality depends on the input. High-contrast images where the subject clearly stands out from the background produce the cleanest results. Images with subject colors similar to the background may have imperfect edges. For product photography, shooting against a solid color (white or gray) still gives the best AI results. For portraits, well-lit subjects with reasonable background separation work reliably. Very complex scenes with multiple overlapping subjects may require manual refinement.
Frequently Asked Questions
How does the AI background removal work?
Krunkit uses RMBG-1.4, an advanced AI segmentation model that runs entirely in your browser via WebGPU/WASM. It analyzes the image to identify the foreground subject and creates a precise mask to remove the background.
Is it really free? What's the catch?
Yes, completely free with no watermarks or limits. The AI model runs in your browser, so there are no server costs. Your images are never uploaded anywhere.
Why does the first use take longer?
The AI model (~44MB) needs to be downloaded once. After that, it's cached by your browser and loads instantly on future visits.
What image types are supported?
JPEG, PNG, WebP, and AVIF images up to 50MB each. The output is always PNG to preserve transparency. You can optionally choose a solid background color.
Can I process multiple images at once?
Yes! Drop up to 10 images at once for batch processing. Each image is processed independently, and you can download all results as a single ZIP file.
Does it work on phones and tablets?
Yes, it works on modern mobile browsers. Processing may be slower on lower-end devices due to the AI computation involved.