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Found 9 papers, 6 papers with code
MSECNet: Accurate and Robust Normal Estimation for 3D Point Clouds by Multi-Scale Edge Conditioning
MSECNet consists of a backbone network and a multi-scale edge conditioning (MSEC) stream.
Diffusion Unit: Interpretable Edge Enhancement and Suppression Learning for 3D Point Cloud Segmentation
Second, we experimentally observe and verify the edge enhancement and suppression behavior.
Ranked #3 on
3D Part Segmentation
on ShapeNet-Part
Enhancing Local Geometry Learning for 3D Point Cloud via Decoupling Convolution
Modeling the local surface geometry is challenging in 3D point cloud understanding due to the lack of connectivity information.
Enhancing Local Feature Learning Using Diffusion for 3D Point Cloud Understanding
Learning point clouds is challenging due to the lack of connectivity information, i. e., edges.
Enhancing Local Feature Learning for 3D Point Cloud Processing using Unary-Pairwise Attention
We present a simple but effective attention named the unary-pairwise attention (UPA) for modeling the relationship between 3D point clouds.
Spatio-Temporal-Categorical Graph Neural Networks for Fine-Grained Multi-Incident Co-Prediction
Forecasting incident occurrences (e. g. crime, EMS, traffic accident) is a crucial task for emergency service providers and transportation agencies in performing response time optimization and dynamic fleet management.
Forecasting Ambulance Demand with Profiled Human Mobility via Heterogeneous Multi-Graph Neural Networks
Forecasting regional ambulance demand plays a fundamental part in dynamic fleet allocation and redeployment.
GeoFlink: A Framework for the Real-time Processing of Spatial Streams
To enable efficient processing of continuous spatial queries and for the effective data distribution among the Flink cluster nodes, a grid-based index is introduced.
Databases Distributed, Parallel, and Cluster Computing
DeepUrbanEvent: A System for Predicting Citywide Crowd Dynamics at Big Events
Therefore in this study, we aim to extract the “deep” trend only from the current momentary observations and generate an accurate prediction for the trend in the short future, which is considered to be an effective way to deal with the event situations.
