Grid-GCN for Fast and Scalable Point Cloud Learning
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Updated
Mar 19, 2020 - Python
Grid-GCN for Fast and Scalable Point Cloud Learning
PyTorch version for the "Micro-expression Recognition Based on Facial Graph Representation Learning and Facial Action Unit Fusion"
pytorch implementation of graph convolutions for semantic segmentation on ADE20K dataset
GCN with MNE input and preprocessing
Source code of the final course paper "Enhancing Word Embeddings with Graph-Based Text Representations"
Implement model in paper Graph Convolutional Networks with Argument-Aware Pooling for Event Detection
Deep Learning Session at ACM Summer School 2021
[ECCV 2024]Temporary code for "Ad-HGformer: An Adaptive HyperGraph Transformer for Skeletal Action Recognition"
Graph4CTR(GCNs, GATs, HGCNs)
This repository contains the official implementation of the paper titled Multimodal weighted graph representation for information extraction from visually rich documents.
Spatial Temporal Graph Convolutional Networks (ST-GCN) for Skeleton-Based Action Recognition in PyTorch
Predict the number of passengers per plane on some flights
This repository is the PyTorch implementation of the Attention-Enhanced Relational Graph Convolutional Networks method for the task Multi-lingual and Cross-lingual Word-in-Context Disambiguation from SemEval-2021.
My implementation of bayesian graph convolution using torch_geometric.
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