Methods for image segmentation, computer devices, and storage mediums

This invention describes a computer method for precisely outlining different parts of an image, such as identifying objects or regions. It first processes the image through a standard neural network to extract basic features. These features are then fed into a second, "context-switchable" neural network that specifically uses depth information from small areas of the image to understand the scene better, ultimately helping the computer segment the image.

Why it matters: Filed before consumer devices commonly integrated high-quality depth sensors. The claimed use of depth information from hyperpixel districts is now significantly more practical to implement with readily available hardware and improved neural network frameworks.

Status: Not in forceListed as no longer active. The specific reason is not in the record we hold.
How hard to build: SpecializedComplex neural network software system

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