
A Backdoor Attack against 3D Point Cloud Classifiers
Vulnerability of 3D point cloud (PC) classifiers has become a grave conc...
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Adaptive Mutual Supervision for WeaklySupervised Temporal Action Localization
Weaklysupervised temporal action localization aims to localize actions ...
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Point Cloud Distortion Quantification based on Potential Energy for Human and Machine Perception
Distortion quantification of point clouds plays a stealth, yet vital rol...
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Invariant Teacher and Equivariant Student for Unsupervised 3D Human Pose Estimation
We propose a novel method based on teacherstudent learning framework fo...
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SpatioTemporal Graph Scattering Transform
Although spatiotemporal graph neural networks have achieved great empir...
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Learning on AttributeMissing Graphs
Graphs with complete node attributes have been widely explored recently....
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Sampling and Recovery of Graph Signals based on Graph Neural Networks
We propose interpretable graph neural networks for sampling and recovery...
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Graph Cross Networks with Vertex Infomax Pooling
We propose a novel graph cross network (GXN) to achieve comprehensive fe...
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Collaborative Adversarial Learning for RelationalLearning on Multiple Bipartite Graphs
Relational learning aims to make relation inference by exploiting the co...
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Dual Graph Embedding for ObjectTag LinkPrediction on the Knowledge Graph
Knowledge graphs (KGs) composed of users, objects, and tags are widely u...
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Wireless 3D Point Cloud Delivery Using Deep Graph Neural Networks
In typical point cloud delivery, a sender uses octreebased digital vide...
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Control of connectivity and rigidity in prismatic assemblies
How can we manipulate the topological connectivity of a threedimensiona...
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Dynamic Multiscale Graph Neural Networks for 3D SkeletonBased Human Motion Prediction
We propose novel dynamic multiscale graph neural networks (DMGNN) to pre...
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MotionNet: Joint Perception and Motion Prediction for Autonomous Driving Based on Bird's Eye View Maps
The ability to reliably perceive the environmental states, particularly ...
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Collaborative Motion Prediction via Neural Motion Message Passing
Motion prediction is essential and challenging for autonomous vehicles a...
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3D Point Cloud Processing and Learning for Autonomous Driving
We present a review of 3D point cloud processing and learning for autono...
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Damagesensitive and domaininvariant feature extraction for vehiclevibrationbased bridge health monitoring
We introduce a physicsguided signal processing approach to extract a da...
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Efficient and Stable Graph Scattering Transforms via Pruning
Graph convolutional networks (GCNs) have welldocumented performance in ...
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Deterministic and stochastic control of kirigami topology
Kirigami, the creative art of paper cutting, is a promising paradigm for...
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Topological and statistical control of kirigami
Kirigami, the creative art of paper cutting, is a promising paradigm for...
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Symbiotic Graph Neural Networks for 3D Skeletonbased Human Action Recognition and Motion Prediction
3D skeletonbased action recognition and motion prediction are two essen...
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Node Attribute Generation on Graphs
Graph structured data provide twofold information: graph structures and...
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Largescale 3D point cloud representations via graph inception networks with applications to autonomous driving
We present a novel graphneuralnetworkbased system to effectively repr...
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Deep Unsupervised Learning of 3D Point Clouds via Graph Topology Inference and Filtering
We propose a deep autoencoder with graph topology inference and filterin...
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ActionalStructural Graph Convolutional Networks for Skeletonbased Action Recognition
Action recognition with skeleton data has recently attracted much attent...
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3D Point Cloud Denoising via Deep Neural Network based Local Surface Estimation
We present a neuralnetworkbased architecture for 3D point cloud denois...
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Weighted Multiprojection: 3D Point Cloud Denoising with Estimated Tangent Planes
As a collection of 3D points sampled from surfaces of objects, a 3D poin...
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Generalized Value Iteration Networks: Life Beyond Lattices
In this paper, we introduce a generalized value iteration network (GVIN)...
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Signal Representations on Graphs: Tools and Applications
We present a framework for representing and modeling data on graphs. Bas...
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Signal Recovery on Graphs: Random versus Experimentally Designed Sampling
We study signal recovery on graphs based on two sampling strategies: ran...
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Signal Recovery on Graphs: Variation Minimization
We consider the problem of signal recovery on graphs as graphs model dat...
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Siheng Chen
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