Search Results for author:
Found 5 papers, 2 papers with code
Beyond Known Clusters: Probe New Prototypes for Efficient Generalized Class Discovery
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.
Dual Relation Alignment for Composed Image Retrieval
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.
Towards Unified Text-based Person Retrieval: A Large-scale Multi-Attribute and Language Search Benchmark
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
Multimodal Learning for Non-small Cell Lung Cancer Prognosis
This paper focuses on the task of survival time analysis for lung cancer.
DeepMMSA: A Novel Multimodal Deep Learning Method for Non-small Cell Lung Cancer Survival Analysis
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.
