In this paper, a novel three-stream network spatiotemporal attention enhanced features fusion network for action recognition is proposed. Firstly, features fusion stream which includes multi-level features fusion blocks, is designed to train the two streams jointly and complement the two-stream network...
Motivation: 首先现有的方法大多针对grid-based和point-based问题,忽略了segment-level的流量预测。其次GCN比较依赖于Laplace矩阵,通常输入图的邻接矩阵是固定的,而实际上道路graph通常具有时变特性,且过去的研究基本都使用地理距离来表达邻接矩阵,实际上地理上的距离并不能很好的体现位置之间的空间相关性。 Preliminaries: ...
The spatio-temporal fusion network consists of two set of Residual Inception blocks that extract temporal dynamics and a fusion connection for appearance and motion features. The benefits of STFN are: (a) it captures local and global temporal dynamics of complementary data to learn video-wide ...
Finally, ESTM and MEM are seamlessly integrated into a 2D CNN, forming the efficient spatio-temporal network (ESTN), with minimal impact on network parameters and computational costs. Extensive experiments show that ESTN outperforms state-of-the-art methods on datasets like Something V1 & V2 and...
每个像素位置的时空变化程度用attention使得变化和不变的像素位置分别分配较高和较低的权值。通过(4)得到预测日期的特征图,可以自适应地关注融合过程中的时空变化信息。最后,根据(5)对深度语义特征Ft和所得到的特征Fpre进行了集成。(Def是反卷积操作) 鉴别器 ...
In [96], on the other hand, the authors used a model learning-based method, where they first semantically segment multisource data (i.e., image and depth image) using a SegNet network, then fuse their scores using a residual learning approach. 4. Examples on spatiotemporal fusion ...
To overcome this limitation, we propose a novel Spatio-Temporal Self-Attention 3D Network (STSANet) for video saliency prediction, in which multiple Spatio-Temporal Self-Attention (STSA) modules are employed at different levels of 3D convolutional backbone to directly capture long-range relations ...
To improve the prediction accuracy of traffic flow under the influence of nearby time traffic flow disturbance, a dynamic spatiotemporal graph attention network traffic flow prediction model based on the attention mechanism was proposed. Considering the
Ensemble graph neural network model for classification of major depressive disorder using whole-brain functional connectivity The graph convolutional network (GCN), graph attention network (GAT), and GraphSAGE models serve as a base models for the ensemble model that was ... S Venkatapathy,M Votino...
内容提示: DARNet: Dual Attention Ref i nement Network withSpatiotemporal Construction for Auditory AttentionDetectionSheng Yan 1∗ Cunhang Fan 1∗† Hongyu Zhang 1 Xiaoke Yang 1 Jianhua Tao 2Zhao Lv 11 Anhui Province Key Laboratory of Multimodal Cognitive Computations,School of Computer ...