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 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 …
A review on video person re-identification based on deep learning
H Ma, C Zhang, Y Zhang, Z Li, Z Wang, C Wei - Neurocomputing, 2024 - Elsevier
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 …
Pyramid spatial-temporal aggregation for video-based person re-identification
Y Wang, P Zhang, S Gao, X Geng… - Proceedings of the …, 2021 - openaccess.thecvf.com
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 …
Video-based person re-identification with spatial and temporal memory networks
Video-based person re-identification (reID) aims to retrieve person videos with the same
identity as a query person across multiple cameras. Spatial and temporal distractors in …
identity as a query person across multiple cameras. Spatial and temporal distractors in …
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 …
Spatio-temporal representation factorization for video-based person re-identification
Despite much recent progress in video-based person re-identification (re-ID), the current
state-of-the-art still suffers from common real-world challenges such as appearance …
state-of-the-art still suffers from common real-world challenges such as appearance …
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 …
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 …