11 citations · 20 across the 11 of their papers we have counts for
13 papers
Decoupling Spherical Reasoning from Dense Prediction for 360 Depth Estimation
Zhijie Shen, Chunyu Lin, Shuai Zheng +4
The equirectangular projection (ERP) is widely used for panoramic depth estimation, but its spatially varying distortion makes geometry-consistent feature modeling challenging. We…
SphereSOD: Geometry-Structure Coupled Learning for 360 Salient Object Detection
Junsong Zhang, Zhijie Shen, Shuai Zheng +4
360° salient object detection (SOD) aims to accurately segment salient regions across a full field of view. However, equirectangular projection (ERP) introduces severe spatial dist…
Revisiting General Map Search via Generative Point-of-Interest Retrieval
Dong Chen, Shuai Zheng, Haoyang Shao +5
Point-of-Interest (POI) retrieval aims to identify relevant candidates from massive-scale POI databases, serving as a cornerstone for diverse location-based services. However, in g…
Towards Effective and Efficient Graph Alignment without Supervision
Songyang Chen, Youfang Lin, Yu Liu +2
Unsupervised graph alignment aims to find the node correspondence across different graphs without any anchor node pairs. Despite the recent efforts utilizing deep learning-based te…
Towards Pre-trained Graph Condensation via Optimal Transport
Yeyu Yan, Shuai Zheng, Wenjun Hui +5
Graph condensation (GC) aims to distill the original graph into a small-scale graph, mitigating redundancy and accelerating GNN training. However, conventional GC approaches heavil…
Dynamic Graph Condensation
Dong Chen, Shuai Zheng, Yeyu Yan +4
Recent research on deep graph learning has shifted from static to dynamic graphs, motivated by the evolving behaviors observed in complex real-world systems. However, the temporal…
FlexCare: Leveraging Cross-Task Synergy for Flexible Multimodal Healthcare Prediction
Muhao Xu, Zhenfeng Zhu, Youru Li +4
Multimodal electronic health record (EHR) data can offer a holistic assessment of a patient's health status, supporting various predictive healthcare tasks. Recently, several studi…
SiGNN: A Spike-induced Graph Neural Network for Dynamic Graph Representation Learning
Dong Chen, Shuai Zheng, Muhao Xu +2
In the domain of dynamic graph representation learning (DGRL), the efficient and comprehensive capture of temporal evolution within real-world networks is crucial. Spiking Neural N…
Unleashing the potential of GNNs via Bi-directional Knowledge Transfer
Shuai Zheng, Zhizhe Liu, Zhenfeng Zhu +3
Based on the message-passing paradigm, there has been an amount of research proposing diverse and impressive feature propagation mechanisms to improve the performance of GNNs. Howe…
Multi-modal Graph Learning for Disease Prediction
Shuai Zheng, Zhenfeng Zhu, Zhizhe Liu +4
Benefiting from the powerful expressive capability of graphs, graph-based approaches have been popularly applied to handle multi-modal medical data and achieved impressive performa…
CETransformer: Casual Effect Estimation via Transformer Based Representation Learning
Zhenyu Guo, Shuai Zheng, Zhizhe Liu +2
Treatment effect estimation, which refers to the estimation of causal effects and aims to measure the strength of the causal relationship, is of great importance in many fields but…
Multi-modal Graph Learning for Disease Prediction
Shuai Zheng, Zhenfeng Zhu, Zhizhe Liu +3
Benefiting from the powerful expressive capability of graphs, graph-based approaches have achieved impressive performance in various biomedical applications. Most existing methods…
Taking Modality-free Human Identification as Zero-shot Learning
Zhizhe Liu, Xingxing Zhang, Zhenfeng Zhu +3
Human identification is an important topic in event detection, person tracking, and public security. There have been numerous methods proposed for human identification, such as fac…