MORI-RAN: Multi-view Robust Representation Learning via Hybrid Contrastive Fusion. (arXiv:2208.12545v1 [cs.CV])

Multi-view representation learning is essential for many multi-view tasks,
such as clustering and classification. However, there are two challenging
problems plaguing the community: i)how to learn robust multi-view
representation from mass unlabeled data and ii) how to balance the view
consistency and the view specificity. To this end, in this paper, we proposed a
hybrid contrastive fusion algorithm to extract robust view-common
representation from unlabeled data. Specifically, we found that introducing an
additional representation space and aligning representations on this …

arxiv cv fusion hybrid learning representation representation learning