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Dezhong Peng

11 papers hereh-index 355k citations123 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author10
  • last author1

Across the 11 of 11 papers where every author was matched, so the position is known.

fields
  • cs.LG5
  • cs.CV4
  • cs.CL1
  • cs.NE1
same name
  • Dezhong Peng — 6 papers, h 13
  • Dezhong Peng — 5 papers, h 6
  • Dezhong Peng — 3 papers, h 10
  • Dezhong Peng — 2 papers, h 6
  • Dezhong Peng — 1 paper, h 7

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20132023
most citedTwin Contrastive Learning for Online Clustering

152 citations · 181 across the 11 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

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★ 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.CV2017★ 1 cited

Kernel Truncated Regression Representation for Robust Subspace Clustering

Liangli Zhen, Dezhong Peng, Wei Wang +1

Subspace clustering aims to group data points into multiple clusters of which each corresponds to one subspace. Most existing subspace clustering approaches assume that input data…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.