no code implementations • 28 Mar 2024 • Yanglin Feng, Yang Qin, Dezhong Peng, Hongyuan Zhu, Xi Peng, Peng Hu
We observe that the data is challenging and with noisy correspondence due to the sparsity, noise, or disorder of point clouds and the ambiguity, vagueness, or incompleteness of texts, which make existing cross-modal matching methods ineffective for PTM.
1 code implementation • NeurIPS 2023 • Yang Qin, Yuan Sun, Dezhong Peng, Joey Tianyi Zhou, Xi Peng, Peng Hu
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 textual modalities.
no code implementations • 18 Oct 2023 • Yunfan Li, Peng Hu, Dezhong Peng, Jiancheng Lv, Jianping Fan, Xi Peng
The core of clustering is incorporating prior knowledge to construct supervision signals.
1 code implementation • 22 Aug 2023 • Yiding Lu, Yijie Lin, Mouxing Yang, Dezhong Peng, Peng Hu, Xi Peng
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., some intra-cluster samples are wrongly treated as negative pairs.
1 code implementation • 19 Aug 2023 • Yang Qin, Yingke Chen, Dezhong Peng, Xi Peng, Joey Tianyi Zhou, Peng Hu
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.
Ranked #2 on Text based Person Retrieval on ICFG-PEDES (using extra training data)
1 code implementation • 13 Feb 2023 • Xu Wang, Dezhong Peng, Ming Yan, Peng Hu
Thanks to the ISS and CCA, our method could encode the discrimination into the domain-invariant embedding space for unsupervised cross-domain image retrieval.
no code implementations • 26 Jan 2023 • Haobin Li, Yunfan Li, Mouxing Yang, Peng Hu, Dezhong Peng, Xi Peng
Thanks to our dual-stream model, both cluster- and view-specific information could be captured, and thus the instance commonality and view versatility could be preserved to facilitate IMvC.
1 code implementation • CVPR 2023 • Haiyu Zhao, Yuanbiao Gou, Boyun Li, Dezhong Peng, Jiancheng Lv, Xi Peng
Vision Transformers have shown promising performance in image restoration, which usually conduct window- or channel-based attention to avoid intensive computations.
1 code implementation • CVPR 2023 • Yanglin Feng, Hongyuan Zhu, Dezhong Peng, Xi Peng, Peng Hu
Recently, with the advent of Metaverse and AI Generated Content, cross-modal retrieval becomes popular with a burst of 2D and 3D data.
2 code implementations • 21 Oct 2022 • Yunfan Li, Mouxing Yang, Dezhong Peng, Taihao Li, Jiantao Huang, Xi Peng
Specifically, we find that when the data is projected into a feature space with a dimensionality of the target cluster number, the rows and columns of its feature matrix correspond to the instance and cluster representation, respectively.
Ranked #1 on Short Text Clustering on Biomedical
1 code implementation • CVPR 2023 • Pengxin Zeng, Yunfan Li, Peng Hu, Dezhong Peng, Jiancheng Lv, Xi Peng
Fair clustering aims to divide data into distinct clusters while preventing sensitive attributes (\textit{e. g.}, gender, race, RNA sequencing technique) from dominating the clustering.
Ranked #1 on Image Clustering on HAR
1 code implementation • COLING 2022 • Tianyi Lei, Honghui Hu, Qiaoyang Luo, Dezhong Peng, Xu Wang
To address this issue, we propose a novel Adaptive Meta-learner via Gradient Similarity (AMGS) method to improve the model generalization ability to a new task.
1 code implementation • 21 Sep 2020 • Yunfan Li, Peng Hu, Zitao Liu, Dezhong Peng, Joey Tianyi Zhou, Xi Peng
In this paper, we propose a one-stage online clustering method called Contrastive Clustering (CC) which explicitly performs the instance- and cluster-level contrastive learning.
Ranked #4 on Image Clustering on STL-10 (using extra training data)
no code implementations • 7 Jun 2018 • Liangli Zhen, Miqing Li, Ran Cheng, Dezhong Peng, Xin Yao
The redundancy of some objectives can lead to the multiobjective problem having a degenerate Pareto front, i. e., the dimension of the Pareto front of the $m$-objective problem be less than (m-1).
no code implementations • 15 May 2017 • Liangli Zhen, Dezhong Peng, Wei Wang, Xin Yao
Our method has the advantages of a closed-form solution and the capacity of clustering data points that lie on nonlinear subspaces.
no code implementations • 24 Apr 2013 • Liangli Zhen, Zhang Yi, Xi Peng, Dezhong Peng
There are two popular schemes to construct a similarity graph, i. e., pairwise distance based scheme and linear representation based scheme.