CRCNet: few-shot segmentation with cross-reference and region–global conditional networks

• Main Authors: Liu, Weide, Zhang, Chi, Lin, Guosheng, Liu, Fayao
• Other Authors: School of Computer Science and Engineering
• Format: Article
• Language: English
• Published: 2023
• Subjects: Engineering::Computer science and engineering; Few Shot Learning; Semantic Segmentation
• Online Access: https://hdl.handle.net/10356/170422
• Institution: Nanyang Technological University

Few-shot segmentation aims to learn a segmentation model that can be generalized to novel classes with only a few training images. In this paper, we propose a Cross-Reference and Local–Global Conditional Networks (CRCNet) for few-shot segmentation. Unlike previous works that only predict the query i...