activity
20152022
most citedLearning on Attribute-Missing Graphs

126 citations · 402 across the 32 of their papers we have counts for

collaborators

42 papers

cs.CV20221 cited

Number-Adaptive Prototype Learning for 3D Point Cloud Semantic Segmentation

Yangheng Zhao, Jun Wang, Xiaolong Li +4

3D point cloud semantic segmentation is one of the fundamental tasks for 3D scene understanding and has been widely used in the metaverse applications. Many recent 3D semantic segm…

cs.CV202270 cited

Where2comm: Communication-Efficient Collaborative Perception via Spatial Confidence Maps

Yue Hu, Shaoheng Fang, Zixing Lei +2

Multi-agent collaborative perception could significantly upgrade the perception performance by enabling agents to share complementary information with each other through communicat…

cs.CV2022

Hierarchical Spherical CNNs with Lifting-based Adaptive Wavelets for Pooling and Unpooling

Mingxing Xu, Chenglin Li, Wenrui Dai +4

Pooling and unpooling are two essential operations in constructing hierarchical spherical convolutional neural networks (HS-CNNs) for comprehensive feature learning in the spherica…

cs.CV20227 cited

GroupNet: Multiscale Hypergraph Neural Networks for Trajectory Prediction with Relational Reasoning

Chenxin Xu, Maosen Li, Zhenyang Ni +2

Demystifying the interactions among multiple agents from their past trajectories is fundamental to precise and interpretable trajectory prediction. However, previous works only con…

cs.DC2022

Energy-Efficient Computation Offloading in MobileEdge Computing Systems with Uncertainties

Tianxi Ji, Changqing Luo, Lixing Yu +4

Computation offloading is indispensable for mobile edge computing (MEC). It uses edge resources to enable intensive computations and save energy for resource-constrained devices. E…

cs.CV20211 cited

Collaborative Uncertainty in Multi-Agent Trajectory Forecasting

Bohan Tang, Yiqi Zhong, Ulrich Neumann +3

Uncertainty modeling is critical in trajectory forecasting systems for both interpretation and safety reasons. To better predict the future trajectories of multiple agents, recent…