A multi-branch attention fusion module (MAFM) uses positional encoding to add position information. Additionally, multi-branch aggregation attention (MAA) in the MAFM fully fuses the same level of deep features extracted by ResNet50 and the Swin transformer, which enhances the boundary s...
Specifically, we first achieve preliminary feature refinement through a backbone network with a non-local attention mechanism. Then, a two-level multi-branch architecture in MBA-Net is proposed with two-level features refinement to obtain aware local discriminative features from the self-attention ...
在每个阶段中,使用一个包含多尺度图像块嵌入模块(Multi-scale Patch Embedding)和多支路 Transformer 块(Multi-branch Transformer Block)的残差结构块。 多尺度图像块嵌入模块用来生成多尺度的 token 标记,然后分别将它们输入到多个 Transformer 支路中。每个 Transformer 支路包含多个Transformer编码器,并在多支路 Transform...
为了解决这个问题,提出了一种用于三维目标检测的多分支深度融合网络(Multi-Branch Deep Fusion Network, MBDF-Net)。与以往基于双分支的方法不同,该模型由三个分支组成,分别为图像分支、激光雷达分支和融合分支。图像分支和激光雷达分支用于提取相应数据形态的语义信息。利用几个自适应注意力融合(AAF)模块为融合分支生成...
First, attention branch and multi-scale branch are designed respectively. In the attention branch, we design shade module, random erasing module and stepped module, and guide each module to learn discriminative features of different regions through the consistent activation penalty function. In the ...
Multi-Context Attention for Human Pose Estimation abstract 在本文中,我们提出将卷积神经网络与多上下文注意机制结合到一个端到端人体姿态估计框架中。我们采用堆叠的hourglass网络,以不同语义的多分辨率特征生成注意力maps。利用条件随机场
attention weights for each target class. Then 12 different context vectors are obtained by calculating the inner product of\({y}_{i}\)and each attention weight. It is expected that these vectors can well compress the important information needed for each prediction branch. The Multi-label ...
Many state-of-the-art low-light image enhancement techniques now suffer from issues like color distortion, detail blurring, and the halo effect, hindering their ability to produce visual effects. This paper presents a multi-branch low-light enhancement algorithm based on spatial transformation to sig...
图上展示的1 way-1 shot的任务,实际处理时,每个support branch分支的attention RPN、detector不共享。而多个shot时,计算每一个类别的support feature是取了所有feature的平均。 Problem Definition 作者将小样本目标检测目标定义为:给定少量包含novel object的support集合,需要检测出包含所有该novel object category的前景...
Multi-branch Segmentation-guided Attention Network for crowd counting Journal of Visual Communication and Image Representation, Volume 97, 2023, Article 103964 Zheyi Fan,…, Yixuan Zhu TheLR531v1 – A deep learning multi-branch CNN architecture for day-night automatic segmentation of horticultural crops...