17 accepted papers
Multi-view clustering (MVC) adopts complementary information from multiple views to reveal the underlying structure of the data. However, the conventional MVC-based methods remain a crucial challenge on the incomplete multi-view clustering (IMVC) tasks, when some views of the multi-view data are mis…
While existing incomplete multi-view multi-label learning methods have achieved promising performance, few studies have focused on the issue of multi-view imbalance. Existing methods using gradient modulation or alternating optimization strategies alleviate this problem but often oversimplify the in
The objective of referring expression comprehension (REC) is to accurately identify the object in an image described by a given expression. Existing REC methods, including transformer-based and graph-based approaches among others, have shown robust performance in REC tasks. In this study, we present…
Current existing clustering methods for handling incomplete multi-view data primarily concentrate on learning a common representation or graph from the available views, while overlooking the latent information contained in the missing views and the imbalance of information among different views. Fur
Palm-vein has received widespread attention for reliable biometric recognition due to its robust resistance to replicate and forge. However, the rise of adversarial attacks poses a high risk of vulnerability for palm-vein recognition, leaving most existing methods vulnerable to small and human-imper…
Incomplete multi-view clustering (IMVC) aims to reveal shared clustering structures within multi-view data, where only partial views of the samples are available. Existing IMVC methods primarily suffer from two issues: 1) Imputation-based methods inevitably introduce inaccurate imputations, which in…
As a branch of clustering, multi-view clustering has received much attention in recent years. In practical applications, a common phenomenon is that partial views of some samples may be missing in the collected multi-view data, which poses a severe challenge to design the multi-view learning model a…
Graph-based multi-view clustering has attracted extensive attention because of the powerful clustering-structure representation ability and noise robustness. Considering the reality of a large amount of incomplete data, in this paper, we propose a simple but effective method for incomplete multi-vie…
Most of the existing incomplete multi-view clustering (IMVC) methods focus on attaining a consensus representation from different views but ignore the important information hidden in the missing views and the latent intrinsic structures in each view. To tackle these issues, in this paper, a unified…
Low-rank based methods have been widely adopted to structure preserving, when the projection matrix is learned for feature extraction. However, some dilemmas still exist that degrade the classification performance: 1) The local structure of the data is ignored; 2) the reconstructed data is not consi…
Incomplete multi-view clustering has attracted increasing attentions due to its superiority in partitioning unlabeled multi-view data with missing instances in real application. However, most existing methods cannot fully exploit both the view-specific and cross-view relations among data points and…
Cross-modal hashing has received increasing research attentions due to its less storage and efficient retrieval. However, most existing cross-modal hashing methods focus only on exploring multi-modal information, while underestimate the significance of local and Euclidean structure information on th…
Human age estimation from face image has drawn increasing research attention due to its many meaningful applications such as demographics analysis and surveillance monitoring. However, most existing methods directly extract age-specific features for age estimation and ignore age-related gender infor…
In this paper, we propose a novel method, referred to as incomplete multi-view tensor spectral clustering with missing-view inferring (IMVTSC-MVI) to address the challenging multi-view clustering problem with missing views. Different from the existing methods which commonly focus on exploring the ce…
In recent years, incomplete multi-view clustering, which studies the challenging multi-view clustering problem on missing views, has received growing research interests. Although a series of methods have been proposed to address this issue, the following problems still exist: 1) Almost all of the ex…
Direction information has been intensively investigated for Finger-Knuckle-Print (FKP) recognition. However, most existing direction-based KFP recognition methods are handcrafted, which are heuristic and require too much prior knowledge to engineer them. In this paper, we propose a discriminative di…
Palmprint recognition is an important and widely used biometric modality with high reliability, stability and user acceptability. In this paper we propose a simple and effective ensemble learning method for palmprint identification based on Random Subspace Sampling (RSS). To achieve it, we rely on 2…