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A survey on hypergraph neural networks: An in-depth and step-by-step guide
Higher-order interactions (HOIs) are ubiquitous in real-world complex systems and
applications. Investigation of deep learning for HOIs, thus, has become a valuable agenda …
applications. Investigation of deep learning for HOIs, thus, has become a valuable agenda …
Graph neural networks: foundation, frontiers and applications
The field of graph neural networks (GNNs) has seen rapid and incredible strides over the
recent years. Graph neural networks, also known as deep learning on graphs, graph …
recent years. Graph neural networks, also known as deep learning on graphs, graph …
A review on video person re-identification based on deep learning
Abstract Person Re-Identification (ReID) is an essential technology for matching a person
across non-overlap** cameras. It has attracted increasing attention in recent years due to …
across non-overlap** cameras. It has attracted increasing attention in recent years due to …
Deep learning-based person re-identification methods: A survey and outlook of recent works
In recent years, with the increasing demand for public safety and the rapid development of
intelligent surveillance networks, person re-identification (Re-ID) has become one of the hot …
intelligent surveillance networks, person re-identification (Re-ID) has become one of the hot …
TF-CLIP: Learning text-free CLIP for video-based person re-identification
Large-scale language-image pre-trained models have shown superior performances on
many cross-modal retrieval tasks. However, the problem of transferring the knowledge …
many cross-modal retrieval tasks. However, the problem of transferring the knowledge …
Stock selection via spatiotemporal hypergraph attention network: A learning to rank approach
Quantitative trading and investment decision making are intricate financial tasks that rely on
accurate stock selection. Despite advances in deep learning that have made significant …
accurate stock selection. Despite advances in deep learning that have made significant …
Bicnet-tks: Learning efficient spatial-temporal representation for video person re-identification
In this paper, we present an efficient spatial-temporal representation for video person re-
identification (reID). Firstly, we propose a Bilateral Complementary Network (BiCnet) for …
identification (reID). Firstly, we propose a Bilateral Complementary Network (BiCnet) for …
Sheaf hypergraph networks
Higher-order relations are widespread in nature, with numerous phenomena involving
complex interactions that extend beyond simple pairwise connections. As a result …
complex interactions that extend beyond simple pairwise connections. As a result …
Pyramid spatial-temporal aggregation for video-based person re-identification
Video-based person re-identification aims to associate the video clips of the same person
across multiple non-overlap** cameras. Spatial-temporal representations can provide …
across multiple non-overlap** cameras. Spatial-temporal representations can provide …
Salient-to-broad transition for video person re-identification
Due to the limited utilization of temporal relations in video re-id, the frame-level attention
regions of mainstream methods are partial and highly similar. To address this problem, we …
regions of mainstream methods are partial and highly similar. To address this problem, we …