Dual-stream Network 如图一所示, 双流网络通常用于处理多模态数据的应用程序中。通过分别处理数据的每种模态,网络可以学习特定于每种模态的特征,然后可以融合这些特征以获得更全面的数据表示。在面对反欺骗任务时,可以采用双流网络分别处理rgb和depth输入,然后融合提取的特征,提高分类的整体准确率。我们使用的双流结构有两...
学会“成果速览”系列文章旨在将图像图形领域会议期刊重要成果进行传播,通过短篇文章让读者用母语快速了解相关学术动态,欢迎关注和投稿~ ◆◆◆ 双流图像表征网络(Dual-stream Network)Mingyuan Mao , Peng Gao , Renrui Zhang , Honghui Zheng ...
具有显著的全局表示能力的Transformer在视觉任务中获得了具有竞争性的结果,但在输入图像中没有考虑到高层及的局部特征信息。在本论文中,我们提出了一种通用的双流网络(Dual-stream Network, DS-Net)以充分挖掘图像分类中局部和全局特征的表征容量。我们的DS-Net可以同时计算细粒度和集成的特征,并有效地融合它们。具体地...
Dual-stream networkMulti-scale fusionScale context selection attentionThe fusion of multi-scale features has been an effective method to get state-of-the-art performance in semantic segmentation. In this work, we concentrate on two tricky problems鈥攖he intra-class inconsistency and the blur on ...
we present a neural network model that ad-dresses the challengesposed byRaven’sProgressiveMatrices(RPM). Inspired by the two-stream hypothesis of visual pro-cessing, we introduce the Dual-stream Reasoning Network(DRNet), which utilizes two parallel branches to capture im-age features. On top ...
In this paper, we present a generic Dual-stream Network (DS-Net) to fully explore the representation capacity of local and global pattern features for image classification. Our DS-Net can simultaneously calculate fine-grained and integrated features and efficiently fuse them. Specifically, we ...
To alleviate these issues, a novel approach, named Dual-Stream Network (DSNet), is proposed in this paper for FGSC. DSNet consists of two sub-branches: the Local Residual Branch (LRB) and the Global Representation Branch (GRB). Specifically, the LRB effectively extracts the most ...
convolutional neural networktime domainfrequency domainwearable sensorsWith the increasing awareness of health, using wearable sensors to monitor individual activities and accurately estimate energy expenditure has become a current research focus. However, existing research encounters challenges including low ...
Dual-stream Network for Visual Recognition 5.31 挂在arxiv tips: 看完这篇文章后,感觉收获了蛮多。先是一些心得: 1.首先是,vit现在的工作中,有蛮多工作在做,利用transformer解耦两个尺度的特征,自然的有一个问题就是怎么融合。之前的如comformer给出了FCU,来进行两个style的特征融合。做法是先直接对齐通道数...
Here, we build a 'dual-stream' neural network model which, equipped with both dorsal and ventral streams, can generalise its counting ability to wholly novel items ('zero-shot' counting). In doing so, it forms spatial response fields and lognormal number codes that resemble those observed in...