1 code implementation • 13 Apr 2024 • Ye Wang, Yaxiong Wang, Yujiao Wu, Bingchen Zhao, Xueming Qian
To counteract this inefficiency, we opt to cluster only the unlabelled instances and subsequently expand the cluster prototypes with our introduced potential prototypes to fast explore novel classes.
no code implementations • 5 Sep 2023 • Xintong Jiang, Yaxiong Wang, Yujiao Wu, Meng Wang, Xueming Qian
Unlike the general image-text retrieval problem with only one alignment relation, i. e., image-text, we argue for the existence of two types of relations in composed image retrieval.
1 code implementation • 5 Jun 2023 • Shuyu Yang, Yinan Zhou, Yaxiong Wang, Yujiao Wu, Li Zhu, Zhedong Zheng
To verify the feasibility of learning from the generated data, we develop a new joint Attribute Prompt Learning and Text Matching Learning (APTM) framework, considering the shared knowledge between attribute and text.
Ranked #1 on Text based Person Retrieval on CUHK-PEDES
no code implementations • 7 Nov 2022 • Yujiao Wu, Yaxiong Wang, Xiaoshui Huang, Fan Yang, Sai Ho Ling, Steven Weidong Su
This paper focuses on the task of survival time analysis for lung cancer.
no code implementations • 12 Jun 2021 • Yujiao Wu, Jie Ma, Xiaoshui Huang, Sai Ho Ling, Steven Weidong Su
To improve the survival prediction accuracy and help prognostic decision-making in clinical practice for medical experts, we for the first time propose a multimodal deep learning method for non-small cell lung cancer (NSCLC) survival analysis, named DeepMMSA.