3 accepted papers
The feature dispersion, arising from the inherent constraints of data scarcity, has emerged as a prominent challenge in the domain of few-shot learning. In this paper, we propose a novel Self-adaptive Distribution Regularization (SADR) approach, which can adaptively bridge the semantic gaps across d…
Cross-modal hashing has garnered considerable research interest due to its rapid retrieval and low storage costs. However, the majority of existing methods suffer from the limitations of context loss and information redundancy, particularly in simulated textual environments enriched with manually an…
Medical vision-language representation learning has garnered considerable attention owing to its applicability to extracting generic representations from the image and text modality. However, it still remains challenging to acquire a more comprehensive understanding of intra- and inter-modal semanti…