1 code implementation • 12 Jun 2023 • Mengke Li, Zhikai Hu, Yang Lu, Weichao Lan, Yiu-ming Cheung, Hui Huang
To rectify this issue, we propose to augment tail classes by grafting the diverse semantic information from head classes, referred to as head-to-tail fusion (H2T).
1 code implementation • 18 May 2023 • Mengke Li, Yiu-ming Cheung, Yang Lu, Zhikai Hu, Weichao Lan, Hui Huang
Based on these perturbed features, two novel logit adjustment methods are proposed to improve model performance at a modest computational overhead.
1 code implementation • 4 May 2018 • Xin Liu, Zhikai Hu, Haibin Ling, Yiu-ming Cheung
More specifically, MTFH exploits an efficient objective function to flexibly learn the modality-specific hash codes with different length settings, while synchronously learning two semantic correlation matrices to semantically correlate the different hash representations for heterogeneous data comparable.