Invention Application
- Patent Title: Patch-Based Image Matting Using Deep Learning
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Application No.: US17696377Application Date: 2022-03-16
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Publication No.: US20220207751A1Publication Date: 2022-06-30
- Inventor: Ning XU
- Applicant: ADOBE INC.
- Applicant Address: US CA San Jose
- Assignee: ADOBE INC.
- Current Assignee: ADOBE INC.
- Current Assignee Address: US CA San Jose
- Main IPC: G06T7/194
- IPC: G06T7/194 ; G06T5/50 ; G06N3/04 ; G06N3/08

Abstract:
Methods and systems are provided for generating mattes for input images. A neural network system is trained to generate a matte for an input image utilizing contextual information within the image. Patches from the image and a corresponding trimap are extracted, and alpha values for each individual image patch are predicted based on correlations of features in different regions within the image patch. Predicting alpha values for an image patch may also be based on contextual information from other patches extracted from the same image. This contextual information may be determined by determining correlations between features in the query patch and context patches. The predicted alpha values for an image patch form a matte patch, and all matte patches generated for the patches are stitched together to form an overall matte for the input image.
Public/Granted literature
- US11978216B2 Patch-based image matting using deep learning Public/Granted day:2024-05-07
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