activity
20172022
most citedDisentangled Graph Neural Networks for Session-based Recommendation

11 citations · 24 across the 6 of their papers we have counts for

collaborators

7 papers

cs.IR202211 cited

Disentangled Graph Neural Networks for Session-based Recommendation

Ansong Li, Zhiyong Cheng, Fan Liu +3

Session-based recommendation (SBR) has drawn increasingly research attention in recent years, due to its great practical value by only exploiting the limited user behavior history…

cs.CV2021

A Novel Patch Convolutional Neural Network for View-based 3D Model Retrieval

Zan Gao, Yuxiang Shao, Weili Guan +3

Recently, many view-based 3D model retrieval methods have been proposed and have achieved state-of-the-art performance. Most of these methods focus on extracting more discriminativ…

cs.CV20212 cited

Multigranular Visual-Semantic Embedding for Cloth-Changing Person Re-identification

Zan Gao, Hongwei Wei, Weili Guan +3

Person reidentification (ReID) is a very hot research topic in machine learning and computer vision, and many person ReID approaches have been proposed; however, most of these meth…

cs.CV20215 cited

TBNet:Two-Stream Boundary-aware Network for Generic Image Manipulation Localization

Zan Gao, Chao Sun, Zhiyong Cheng +3

Finding tampered regions in images is a hot research topic in machine learning and computer vision. Although many image manipulation location algorithms have been proposed, most of…

cs.IR20212 cited

Interest-aware Message-Passing GCN for Recommendation

Fan Liu, Zhiyong Cheng, Lei Zhu +2

Graph Convolution Networks (GCNs) manifest great potential in recommendation. This is attributed to their capability on learning good user and item embeddings by exploiting the col…

cs.CV20204 cited

Multiple Discrimination and Pairwise CNN for View-based 3D Object Retrieval

Z. Gao, K. X Xue, S. H Wan

With the rapid development and wide application of computer, camera device, network and hardware technology, 3D object (or model) retrieval has attracted widespread attention and i…