因此,本文基于图像的图表示(graph representation)提出了 vision graph neural network (ViG)。本文应该是首次将图神经网络用于视觉任务,同时能取得很好的效果,在 ImageNet 分类任务上超过了 CNN (ResNet), MLP (CycleMLP) 和 transformer (Swin-T) 。 方法 2.1 ViG Block 2.1.1 Graph Representation of Image ...
因此,本文基于图像的图表示(graph representation)提出了vision graph neural network (ViG)。本文应该是首次将图神经网络用于视觉任务,同时能取得很好的效果,在imagenet分类任务上超过了CNN(ResNet),MLP(CycleMLP)和transformer(Swin-T)。 方法 2.1 ViG Block 2.1.1 Graph Representation of Image 对于一张图片,首先...
In this paper, we introduce a novel Windowed vision Graph neural Network (WiGNet) model for efficient image processing. WiGNet explores a different strategy from previous works by partitioning the image into windows and constructing a graph within each window. Therefore, our model uses graph ...
[25]Yongcheng Jing, Yining Mao, Yiding Yang, Yibing Zhan, Mingli Song, Xinchao Wang, and Dacheng Tao. Learning graph neural networks for image style transfer. InECCV, 2022. [26]Thomas N Kipf and Max Welling. Semi-supervised classification with graph convolutional networks. In ICLR, 2017. [...
Graph Neural Networks (GNNs): 一些工作利用图神经网络来学习网络表示,以改进处理神经网络的方法。 Data Augmentation in Weight Spaces: 为了提高处理神经网络的方法的泛化能力,有研究探索了直接在权重空间中进行数据增强的各种策略。 这些相关研究表明,连接NeRF、图像和文本的研究方向是建立在多个领域现有工作的基础上的...
W. et al. Relational inductive biases, deep learning, and graph networks. Preprint at http://arxiv.org/abs/1806.01261 (2018). Scarselli, F., Gori, M., Tsoi, A. C., Hagenbuchner, M. & Monfardini, G. The graph neural network model. IEEE Trans. Neural Netw. 20, 61–80 (2009)....
Neural network visualization and interpretability(神经网络可视化与可解释性) Similarity Learning(相似度与度量学习) Attention and transformers(注意力与transformer) Graph neural networks(图神经网络) Autoencoders & VAE(自编码器与VAE) Generative models I(生成模型与GAN I) ...
Taken From Article, Graph Neural Networks in Computer Vision Comparing different versions of the Inception Architecture Over the years, the Inception architecture has evolved to address various limitations and improve its performance on computer vision tasks. Here are some of the main versions of th...
Spektral is a Python library for graph deep learning, based on the Keras API and TensorFlow 2. The main goal of this project is to provide a simple but flexible framework for creating graph neural networks (GNNs). You can use Spektral for classifying the users of a social network, predictin...
doi_only_gnn_cv_network_file_citation_refs.txt Add files via upload May 23, 2022 View all files Repository files navigation README Graph Neural Networks in Computer Vision - Architectures Datasets and Common Approaches About Graph Neural Networks in Computer Vision - Architectures, Datasets...