Counterfactual context-aware texture learning for camouflaged object detection

US12136261B2 · kind B2 · utility

Assignee

• NATIONAL UNIVERSITY OF DEFENSE TECHNOLOGY · CN

Inventors

• Shuohao Li · Hunan, CN
• Xiaofei Li · Beijing, CN
• Jun Zhang · Longbeilingcun, CN
• Kuihua Huang · Hunan, CN
• Chao-Yeh Chen · Austin, US
• Boliang Sun · Hunan, CN
• Jun Lei · Qingdao, CN
• Miaomiao Yu · Hunan, CN

Key dates

• Filing date: Apr 24, 2024
• Grant date: Nov 5, 2024
• Expiry date: Apr 24, 2044

Classification

• Technology area (CPC G): Physics
• CPC primary: G06V10/82
• WIPO field: Computer technology
• WIPO sector: Electrical engineering

Abstract

A counterfactual context-aware texture learning network system, including: a camera configured to capture an input image; a processor configured to perform camouflaged object detection on the input image; and a memory configured to store a texture-aware refinement module (TRM), a context-aware fused module (CFM), and a counterfactual intervention module (CIM); wherein the processor is configured to execute program instructions of the TRM, the CFM, and the CIM; the TRM is configured to extract dimension features from the input image; the CFM is configured to infuse multi-scale contextual features; the CIM is configured to identify a camouflaged object with counterfactual intervention via the processor; the TRM includes: a receptive field block (RFB) configured to expand a receptive field and extract texture features; and a position attention module (PAM) and a channel attention module (CAM) configured to further refine texture-aware features and obtain discriminant feature representation.