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20202025
most citedSemantic Invariant Multi-view Clustering with Fully Incomplete Information

63 citations · 108 across the 13 of their papers we have counts for

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Showing 2023Show all

7 papers · 1 filter

cs.CV2023★ 7 cited

Cross-modal Active Complementary Learning with Self-refining Correspondence

Yang Qin, Yuan Sun, Dezhong Peng +3

Recently, image-text matching has attracted more and more attention from academia and industry, which is fundamental to understanding the latent correspondence across visual and te…

cs.LG2023★ 4 cited

Image Clustering with External Guidance

Yunfan Li, Peng Hu, Dezhong Peng +3

The core of clustering is incorporating prior knowledge to construct supervision signals. From classic k-means based on data compactness to recent contrastive clustering guided by…

cs.CV2023★ 4 cited

Decoupled Contrastive Multi-View Clustering with High-Order Random Walks

Yiding Lu, Yijie Lin, Mouxing Yang +3

In recent, some robust contrastive multi-view clustering (MvC) methods have been proposed, which construct data pairs from neighborhoods to alleviate the false negative issue, i.e.…

cs.CV2023★ 2 cited

Noisy-Correspondence Learning for Text-to-Image Person Re-identification

Yang Qin, Yingke Chen, Dezhong Peng +3

Text-to-image person re-identification (TIReID) is a compelling topic in the cross-modal community, which aims to retrieve the target person based on a textual query. Although nume…

cs.CV2023★ 63 cited

Semantic Invariant Multi-view Clustering with Fully Incomplete Information

Pengxin Zeng, Mouxing Yang, Yiding Lu +3

Robust multi-view learning with incomplete information has received significant attention due to issues such as incomplete correspondences and incomplete instances that commonly af…

cs.CV2023★ 3 cited

Correspondence-Free Domain Alignment for Unsupervised Cross-Domain Image Retrieval

Xu Wang, Dezhong Peng, Ming Yan +1

Cross-domain image retrieval aims at retrieving images across different domains to excavate cross-domain classificatory or correspondence relationships. This paper studies a less-t…

cs.LG2023★ 2 cited

Incomplete Multi-view Clustering via Prototype-based Imputation

Haobin Li, Yunfan Li, Mouxing Yang +3

In this paper, we study how to achieve two characteristics highly-expected by incomplete multi-view clustering (IMvC). Namely, i) instance commonality refers to that within-cluster…