作者:Guangyu Huo, Yong Zhang, Junbin Gao, Boyue Wang, Yongli Hu, Baocai Yin 发表时间:2021年1月 论文地址:https://arxiv.org/pdf/2101.06883.pdf 目录 论文阅读06——《CaEGCN: Cross-Attention Fusion based Enhanced Graph Convolutional Network for Clustering》 Ideas: Model: 交叉注意力融合模块 图自...
Feature crossKnowledge Graph has attracted a wide range of attention in the field of recommendation, which is usually applied as auxiliary information to solve the problem of data sparsity. However, most recommendation models cannot effectively mine the associations between the items to be recommended ...
因此,BEVFusion中提出在拼接后的BEV特征上进行一些卷积操作,以消除局部的对齐误差。 BEVFusion的融合流程 在2.2节中我们介绍了两种不同的query生成策略:稠密 vs. 稀疏。BEVFusion中采用的是稠密的query策略,每个传感器都生成了BEV特征,再进行融合。同样的,特征融合也可以在稀疏query的基础上进行,也就是在目标级别上进...
Cross-Attention Fusion:利用 CLS 来交互信息。 Cross-Attention Fusion 将CLS 当成是一个分支的抽象信息,那么只需要交换两个分支的 CLS,然后送入 Transformer 中,两个分支的信息就可以进行交互了,这样有助于在另一个分支中引入不同尺度的信息image-20230614214151778上...
Knowledge Graph has attracted a wide range of attention in the field of recommendation, which is usually applied as auxiliary information to solve the problem of data sparsity. However, most recommendation models cannot effectively mine the associations between the items to be recommended and the enti...
1.Rethinking Cross-Attention for Infrared and Visible Image Fusion 方法:本文提出了一种端到端的ATFuse网络,用于融合红外图像。通过在交叉注意机制的基础上引入差异信息注入模块(DIIM),可以分别探索源图像的独特特征。同时,作者还应用了交替公共信息注入模块(ACIIM),以充分保留最终结果中的公共信息。为了训练ATFuse...
Cross-Attention Fusion:利用 CLS 来交互信息。 Cross-Attention Fusion 将CLS 当成是一个分支的抽象信息,那么只需要交换两个分支的 CLS,然后送入 Transformer 中,两个分支的信息就可以进行交互了,这样有助于在另一个分支中引入不同尺度的信息 上图为实例,就是使用一个 Transformer block 来生成新的 CLS。例子是...
class Attention(nn.Module): def __init__(self, dim, num_heads, bias): super(Attention, self).__init__() self.num_heads = num_heads self.temperature = nn.Parameter(torch.ones(num_heads, 1, 1)) self.qkv = nn.Conv2d(dim, dim*3, kernel_size=1, bias=bias) self.qkv...
The cross-attention mechanism is not only fast in training, but also takes up very little GPU. This paper proposes a multi-graph convolution and cross-attention fusion mechanism for traffic flow prediction, to better solve the multi-layer temporal and heterogeneous spatial correlation in the road ...
low-light enhancement; exposure image generator; cross-attention fusion; recursive calculation1. Introduction With the rapid development of computer vision technology, images are widely used in the fields of surveillance equipment, satellite remote sensing, and medical imaging. However, in the process ...