AI Image Matching
Match two views of a scene with neural keypoint extraction and matching, score-colored correspondence lines, and a confidence filter.
Find corresponding points between two photos of the same scene with a neural keypoint extractor and a separate neural matcher. Pixlane runs both inference sessions in your browser and draws score-colored correspondence lines across a side-by-side view.
How to Use AI Image Matching
- Upload an image: Upload one of the formats listed by the tool (JPG, PNG, WebP) and wait for the local preview.
- Adjust settings and process: Upload the second view, choose model resolution and confidence, then run the two-stage matching pipeline.
- Review and download: Review the result, then download it in one of the formats offered by this tool.
Frequently asked questions
What is neural feature matching?
A neural feature pipeline finds distinctive locations in each image and connects locations that appear to represent the same physical point across the two views.
How does the neural matching pipeline work?
A keypoint extractor first describes distinctive locations in each image. A separate matcher session then scores which locations correspond across the two views.
What do the line colors mean?
Line color represents the match confidence: green is higher confidence, yellow is intermediate, and red is the weakest match retained by the selected confidence threshold.
Are my photos uploaded anywhere?
Supported image content is not uploaded for processing. The two model packages total about 50 MB and can be cached after download; inference runs in your browser.