Google patents image repair tool that blends user hints with AI predictions
This patent describes a method for fixing damaged or hidden parts of an image, a process known as inpainting. It uses a computer model to guess what the missing area should look like and combines that guess with specific areas a user has marked as important. The system then blends these two pieces of information to create a more realistic replacement for the missing part.
In the filing’s own words
Systems and methods for augmenting data can leverage one or more machine-learned models and contextual attention data to provide more realistic and efficient data augmentation. For example, systems and methods for inpainting can leverage a machine-learned model to generate predicted contextual attention data and blend the predicted contextual attention data with obtained contextual attention data to determine replacement data for augmenting an image to replace one or more occlusions. The obtained contextual attention data can include user-guided contextual attention.
What exactly they claim (claim 1)
1. A computer-implemented method for training an inpainting model, the method comprising: receiving, by a computing system comprising one or more processors, an input image and a ground truth image, wherein the ground truth image depicts a scene, and wherein the input image depicts the scene with one or more occlusions; processing, by the computing system, the ground truth image with a contextual attention model to generate a contextual attention output; processing, by the computing system, the input image and the contextual attention output with an augmentation model to generate a prediction image, wherein processing the input image and the contextual attention output with the augmentation model comprises: processing the input image to generate predicted contextual attention data; generating blended data based on the predicted contextual attention data and the contextual attention output; generating the prediction image based on the blended data and the input image; evaluating, by the computing system, a loss function that evaluates a difference between the prediction image and the ground truth image; and adjusting, by the computing system, one or more parameters of the augmentation model based at least in part on the loss function.
Facts
- Company
- Google (Google LLC)
- Official title
- Guided contextual attention map for inpainting tasks
- Patent number
- US12743755B2
- Application number
- 18580507
- Filed
- Jul 19, 2021
- Granted
- Sep 22, 2026
- Inventors
- 4
- Claims
- 7
Classified under
G06T 5/77 Physics & computingG06T 5/60 Physics & computingG06T 2207/20081 Physics & computingG06T 2207/20084 Physics & computingMore from Google in AI & software
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Summaries are simplified from the filing’s own abstract and first claim. A patent filing is not a product announcement.
Patent data and drawings: U.S. Patent and Trademark Office (USPTO). Nebula is not affiliated with or endorsed by the USPTO.