Nvidia patents method to train AI to see objects hidden behind others
Nvidia describes a way to teach computer vision systems to identify the full shape of objects, even when parts are hidden by other items. The process uses existing images to create synthetic examples of occluded objects, which are then used to train a new model to predict the complete outline of an item.
In the filing’s own words
The disclosed method for training a machine learning model for image segmentation includes generating, based on one or more first images and one or more first bounding box prompts, and using a first trained machine learning model, a first predicted amodal mask; generating, based on the first predicted amodal mask, the one or more first images, the one or more first bounding box prompts, and one or more ground truth modal masks, unoccluded object data; generating, based on the unoccluded object data, one or more synthetic images and occluded object data; and performing, based on the one or more synthetic images and the occluded object data, one or more operations to train a second machine learning model to generate a second trained machine learning model, where the second trained machine learning model processes a second image and a second bounding box prompt to generate a second predicted amodal mask.
What exactly they claim (claim 1)
1. A computer-implemented method for training a machine learning model for image segmentation, the method comprising: generating, based on one or more first images and one or more first bounding box prompts, and using a first trained machine learning model, a first predicted amodal mask; generating, based on the first predicted amodal mask, the one or more first images, the one or more first bounding box prompts, and one or more ground truth modal masks, unoccluded object data; generating, based on the unoccluded object data, one or more synthetic images and occluded object data; and performing, based on the one or more synthetic images and the occluded object data, one or more operations to train a second machine learning model to generate a second trained machine learning model, wherein the second trained machine learning model processes a second image and a second bounding box prompt to generate a second predicted amodal mask.
Facts
- Company
- Nvidia (NVIDIA CORPORATION)
- Official title
- AMODAL OBJECT SEGMENTATION AND SYNTHETIC AMODAL DATA GENERATION
- Publication number
- US20260260359A1
- Application number
- 19410873
- Filed
- Dec 5, 2025
- Published
- Sep 3, 2026
- Inventors
- 5
- Claims
- 20
Classified under
G06T 7/12 Physics & computingG06N 20/00 Physics & computingG06T 5/50 Physics & computingG06T 11/60 Physics & computingG06V 10/25 Physics & computingG06T 2207/20221 Physics & computingMore from Nvidia 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.