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07/31/2022
Skeleton-Parted Graph Scattering Networks for 3D Human Motion Prediction
Graph convolutional network based methods that model the body-joints' re...
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04/19/2022
GroupNet: Multiscale Hypergraph Neural Networks for Trajectory Prediction with Relational Reasoning
Demystifying the interactions among multiple agents from their past traj...
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08/25/2021
Multiscale Spatio-Temporal Graph Neural Networks for 3D Skeleton-Based Motion Prediction
We propose a multiscale spatio-temporal graph neural network (MST-GNN) t...
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07/02/2021
Online Multi-Agent Forecasting with Interpretable Collaborative Graph Neural Network
This paper considers predicting future statuses of multiple agents in an...
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12/31/2020
Incremental Embedding Learning via Zero-Shot Translation
Modern deep learning methods have achieved great success in machine lear...
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12/17/2020
Invariant Teacher and Equivariant Student for Unsupervised 3D Human Pose Estimation
We propose a novel method based on teacher-student learning framework fo...
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11/03/2020
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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10/05/2020
Graph Cross Networks with Vertex Infomax Pooling
We propose a novel graph cross network (GXN) to achieve comprehensive fe...
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08/28/2020
Decoupled Variational Embedding for Signed Directed Networks
Node representation learning for signed directed networks has received c...
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03/17/2020
Dynamic Multiscale Graph Neural Networks for 3D Skeleton-Based Human Motion Prediction
We propose novel dynamic multiscale graph neural networks (DMGNN) to pre...
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11/25/2019
Inverse-Transform AutoEncoder for Anomaly Detection
Reconstruction-based methods have recently shown great promise for anoma...
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10/05/2019
Symbiotic Graph Neural Networks for 3D Skeleton-based Human Action Recognition and Motion Prediction
3D skeleton-based action recognition and motion prediction are two essen...
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04/26/2019