- Patent Title: Similarity propagation for one-shot and few-shot image segmentation
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Application No.: US16906954Application Date: 2020-06-19
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Publication No.: US11367271B2Publication Date: 2022-06-21
- Inventor: Mayur Hemani , Siddhartha Gairola , Ayush Chopra , Balaji Krishnamurthy , Jonas Dahl
- Applicant: ADOBE INC.
- Applicant Address: US CA San Jose
- Assignee: ADOBE INC.
- Current Assignee: ADOBE INC.
- Current Assignee Address: US CA San Jose
- Agency: Shook, Hardy & Bacon L.L.P.
- Main IPC: G06K9/62
- IPC: G06K9/62 ; G06V10/46 ; G06K9/46

Abstract:
Embodiments of the present invention provide systems, methods, and computer storage media for one-shot and few-shot image segmentation on classes of objects that were not represented during training. In some embodiments, a dual prediction scheme may be applied in which query and support masks are jointly predicted using a shared decoder, which aids in similarity propagation between the query and support features. Additionally or alternatively, foreground and background attentive fusion may be applied to utilize cues from foreground and background feature similarities between the query and support images. Finally, to prevent overfitting on class-conditional similarities across training classes, input channel averaging may be applied for the query image during training. Accordingly, the techniques described herein may be used to achieve state-of-the-art performance for both one-shot and few-shot segmentation tasks.
Public/Granted literature
- US20210397876A1 SIMILARITY PROPAGATION FOR ONE-SHOT AND FEW-SHOT IMAGE SEGMENTATION Public/Granted day:2021-12-23
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