4 papers
Aligning the True Semantics: Constrained Decoupling and Distribution Sampling for Cross-Modal Alignment
Xiang Ma, Lexin Fang, Litian Xu +1
Cross-modal alignment is a crucial task in multimodal learning aimed at achieving semantic consistency between vision and language. This requires that image-text pairs exhibit simi…
Reliable Cross-modal Alignment via Prototype Iterative Construction
Xiang Ma, Litian Xu, Lexin Fang +2
Cross-modal alignment is an important multi-modal task, aiming to bridge the semantic gap between different modalities. The most reliable fundamention for achieving this objective…
Minding Fuzzy Regions: A Data-driven Alternating Learning Paradigm for Stable Lesion Segmentation
Lexin Fang, Yunyang Xu, Xiang Ma +2
Deep learning has achieved significant advancements in medical image segmentation, but existing models still face challenges in accurately segmenting lesion regions. The main reaso…
Bridging the Modality Gap: Dimension Information Alignment and Sparse Spatial Constraint for Image-Text Matching
Xiang Ma, Xuemei Li, Lexin Fang +1
Many contrastive learning based models have achieved advanced performance in image-text matching tasks. The key of these models lies in analyzing the correlation between image-text…