graph construction

49 papers with code • 0 benchmarks • 3 datasets

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Greatest papers with code

DyNet: The Dynamic Neural Network Toolkit

clab/dynet 15 Jan 2017

In the static declaration strategy that is used in toolkits like Theano, CNTK, and TensorFlow, the user first defines a computation graph (a symbolic representation of the computation), and then examples are fed into an engine that executes this computation and computes its derivatives.

graph construction

Deep Relational Reasoning Graph Network for Arbitrary Shape Text Detection

open-mmlab/mmocr CVPR 2020

In this paper, we propose a novel unified relational reasoning graph network for arbitrary shape text detection.

graph construction Relational Reasoning

Graph Neural Networks for Natural Language Processing: A Survey

graph4ai/graph4nlp 10 Jun 2021

Deep learning has become the dominant approach in coping with various tasks in Natural LanguageProcessing (NLP).

graph construction Graph Representation Learning

Two-Stream Adaptive Graph Convolutional Networks for Skeleton-Based Action Recognition

benedekrozemberczki/pytorch_geometric_temporal CVPR 2019

In addition, the second-order information (the lengths and directions of bones) of the skeleton data, which is naturally more informative and discriminative for action recognition, is rarely investigated in existing methods.

Action Recognition graph construction +1

Visualizing Large-scale and High-dimensional Data

lferry007/LargeVis 1 Feb 2016

We propose the LargeVis, a technique that first constructs an accurately approximated K-nearest neighbor graph from the data and then layouts the graph in the low-dimensional space.

graph construction

EFANNA : An Extremely Fast Approximate Nearest Neighbor Search Algorithm Based on kNN Graph

ZJULearning/nsg 23 Sep 2016

In this paper, we propose EFANNA, an extremely fast approximate nearest neighbor search algorithm based on $k$NN Graph.

graph construction Hierarchical structure

Skeleton-Based Action Recognition with Multi-Stream Adaptive Graph Convolutional Networks

lshiwjx/2s-AGCN 15 Dec 2019

Second, the second-order information of the skeleton data, i. e., the length and orientation of the bones, is rarely investigated, which is naturally more informative and discriminative for the human action recognition.

Action Recognition graph construction +1

COMET: Commonsense Transformers for Automatic Knowledge Graph Construction

atcbosselut/comet-commonsense ACL 2019

We present the first comprehensive study on automatic knowledge base construction for two prevalent commonsense knowledge graphs: ATOMIC (Sap et al., 2019) and ConceptNet (Speer et al., 2017).

graph construction Knowledge Graphs

Learning to Propagate Labels: Transductive Propagation Network for Few-shot Learning

csyanbin/TPN ICLR 2019

The goal of few-shot learning is to learn a classifier that generalizes well even when trained with a limited number of training instances per class.

Few-Shot Image Classification General Classification +1

Learning to Segment 3D Point Clouds in 2D Image Space

Zhang-VISLab/Learning-to-Segment-3D-Point-Clouds-in-2D-Image-Space CVPR 2020

In contrast to the literature where local patterns in 3D point clouds are captured by customized convolutional operators, in this paper we study the problem of how to effectively and efficiently project such point clouds into a 2D image space so that traditional 2D convolutional neural networks (CNNs) such as U-Net can be applied for segmentation.

3D Part Segmentation graph construction