• Publications
  • Influence
NUS-WIDE: a real-world web image database from National University of Singapore
TLDR
The benchmark results indicate that it is possible to learn effective models from sufficiently large image dataset to facilitate general image retrieval and four research issues on web image annotation and retrieval are identified. Expand
Multiple feature hashing for real-time large scale near-duplicate video retrieval
TLDR
This paper presents a novel approach - Multiple Feature Hashing (MFH) to tackle both the accuracy and the scalability issues of NDVR and shows that the proposed method outperforms the state-of-the-art techniques in both accuracy and efficiency. Expand
Multi-cue Correlation Filters for Robust Visual Tracking
TLDR
This paper proposes an efficient multi-cue analysis framework for robust visual tracking by combining different types of features, and constructs multiple experts through Discriminative Correlation Filter and each of them tracks the target independently. Expand
Point-of-Interest Recommendations: Learning Potential Check-ins from Friends
TLDR
This work proposes to learn a set of potential locations that each individual's friends have checked-in before and this individual is most interested in to improve POI recommendation accuracy and address cold-start problem. Expand
Attentive Group Recommendation
TLDR
The AGREE model not only improves the group recommendation performance but also enhances the recommendation for users, especially for cold-start users that have no historical interactions individually. Expand
A Neural Influence Diffusion Model for Social Recommendation
TLDR
A deep influence propagation model is proposed to stimulate how users are influenced by the recursive social diffusion process for social recommendation, with more than 13% performance improvements over the best baselines for top-10 recommendation on the two datasets. Expand
Unified Video Annotation via Multigraph Learning
TLDR
This paper shows that various crucial factors in video annotation, including multiple modalities, multiple distance functions, and temporal consistency, all correspond to different relationships among video units, and hence they can be represented by different graphs, and proposes optimized multigraph-based semi-supervised learning (OMG-SSL), which aims to simultaneously tackle these difficulties in a unified scheme. Expand
Camera Constraint-Free View-Based 3-D Object Retrieval
TLDR
The CCFV removes the constraint of static camera array settings for view capturing and can be applied to any view-based 3-D object database and experimental results show that the proposed scheme can achieve better performance than state-of-the-art methods. Expand
Adaptive Transfer Network for Cross-Domain Person Re-Identification
TLDR
A novel adaptive transfer network (ATNet) for effective cross-domain person re-identification that decomposes the complicated cross- domain transfer into a set of factor-wise sub-transfers and gives ATNet the capability of precise style transfer at factor level and eventually effective transfer across domains. Expand
Deep Representation Learning With Part Loss for Person Re-Identification
TLDR
Experimental results on three person ReID datasets, i.e., Market1501, CUHK03, and VIPeR, show that the proposed deep representation learning procedure named part loss network outperforms existing deep representations. Expand
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