65 citations · 126 across the 4 of their papers we have counts for
6 papers
Campus3D: A Photogrammetry Point Cloud Benchmark for Hierarchical Understanding of Outdoor Scene
Xinke Li, Chongshou Li, Zekun Tong +5
Learning on 3D scene-based point cloud has received extensive attention as its promising application in many fields, and well-annotated and multisource datasets can catalyze the de…
Directed Graph Convolutional Network
Zekun Tong, Yuxuan Liang, Changsheng Sun +2
Graph Convolutional Networks (GCNs) have been widely used due to their outstanding performance in processing graph-structured data. However, the undirected graphs limit their appli…
Efficient Approximation Algorithms for Adaptive Influence Maximization
Keke Huang, Jing Tang, Kai Han +5
Given a social network and an integer , the influence maximization (IM) problem asks for a seed set of nodes from to maximize the expected number of nodes influe…
On Isometry Robustness of Deep 3D Point Cloud Models under Adversarial Attacks
Yue Zhao, Yuwei Wu, Caihua Chen +1
While deep learning in 3D domain has achieved revolutionary performance in many tasks, the robustness of these models has not been sufficiently studied or explored. Regarding the 3…
Efficient Approximation Algorithms for Adaptive Target Profit Maximization
Keke Huang, Jing Tang, Xiaokui Xiao +2
Given a social network , the profit maximization (PM) problem asks for a set of seed nodes to maximize the profit, i.e., revenue of influence spread less the cost of seed select…
Efficient Approximation Algorithms for Adaptive Seed Minimization
Jing Tang, Keke Huang, Xiaokui Xiao +4
As a dual problem of influence maximization, the seed minimization problem asks for the minimum number of seed nodes to influence a required number of users in a given social n…