63 citations · 108 across the 13 of their papers we have counts for
13 papers
LLaVA-ReID: Selective Multi-image Questioner for Interactive Person Re-Identification
Yiding Lu, Mouxing Yang, Dezhong Peng +3
Traditional text-based person ReID assumes that person descriptions from witnesses are complete and provided at once. However, in real-world scenarios, such descriptions are often…
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…
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…
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.…
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…
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…
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…
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…
Deep Fair Clustering via Maximizing and Minimizing Mutual Information: Theory, Algorithm and Metric
Pengxin Zeng, Yunfan Li, Peng Hu +3
Fair clustering aims to divide data into distinct clusters while preventing sensitive attributes (\textit{e.g.}, gender, race, RNA sequencing technique) from dominating the cluster…
OPQ: Compressing Deep Neural Networks with One-shot Pruning-Quantization
Peng Hu, Xi Peng, Hongyuan Zhu +2
As Deep Neural Networks (DNNs) usually are overparameterized and have millions of weight parameters, it is challenging to deploy these large DNN models on resource-constrained hard…
Unsupervised Neural Rendering for Image Hazing
Boyun Li, Yijie Lin, Xiao Liu +3
Image hazing aims to render a hazy image from a given clean one, which could be applied to a variety of practical applications such as gaming, filming, photographic filtering, and…
PSRR-MaxpoolNMS: Pyramid Shifted MaxpoolNMS with Relationship Recovery
Tianyi Zhang, Jie Lin, Peng Hu +2
Non-maximum Suppression (NMS) is an essential postprocessing step in modern convolutional neural networks for object detection. Unlike convolutions which are inherently parallel, t…
Contrastive Clustering
Yunfan Li, Peng Hu, Zitao Liu +3
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. To…