1 code implementation • 12 May 2023 • Zewen Zheng, Guoheng Huang, Xiaochen Yuan, Chi-Man Pun, Hongrui Liu, Wing-Kuen Ling
In this paper, we introduce a quaternion perspective on correlation learning and propose a novel Quaternion-valued Correlation Learning Network (QCLNet), with the aim to alleviate the computational burden of high-dimensional correlation tensor and explore internal latent interaction between query and support images by leveraging operations defined by the established quaternion algebra.
Ranked #19 on Few-Shot Semantic Segmentation on COCO-20i (5-shot)