DWCL anchors all contrastive pairs to the single highest-silhouette view and uses dual quality and discrepancy weights, reporting gains on eight multi-view clustering benchmarks.
Deep multiview clustering by contrasting cluster assignments, in: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp
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DWCL: Dual-Weighted Contrastive Learning for Multi-View Clustering
DWCL anchors all contrastive pairs to the single highest-silhouette view and uses dual quality and discrepancy weights, reporting gains on eight multi-view clustering benchmarks.