no code implementations • 18 May 2024 • Ming Hu, Siyuan Yan, Peng Xia, Feilong Tang, Wenxue Li, Peibo Duan, Lin Zhang, ZongYuan Ge
In this paper, we propose a test-time image adaptation method to enhance the accuracy of the model on test data by simultaneously updating and predicting test images.
no code implementations • 16 Apr 2024 • Jinhui Yuan, Shan Lu, Peibo Duan, Jieyue He
Recently, heterogeneous graph neural networks (HGNNs) have achieved impressive success in representation learning by capturing long-range dependencies and heterogeneity at the node level.
1 code implementation • 23 Nov 2023 • Peng Xia, Xingtong Yu, Ming Hu, Lie Ju, Zhiyong Wang, Peibo Duan, ZongYuan Ge
We explore constructing the class hierarchy into a graph, with its nodes representing the textual or image features of each category.
Fine-Grained Visual Recognition Graph Representation Learning