2026
Mask to Align, Weight to Disambiguate: Reliable Unsupervised Cross-Modal Hashing with Masked-Weight Contrast
CVPR 2026
In unsupervised cross-modal hashing, real world multimodal data often exhibit partial alignment and semantic ambiguity. Dominant modalities can easily bias the fusion process, while semantically related samples may be mistakenly treated as negatives in contrastive learning, leading to unstable optim