Mask-Guided Attention Network for Occluded Pedestrian Detection Yanwei Pang1, Jin Xie1, Muhammad Haris Khan2, Rao Muhammad Anwer2, Fahad Shahbaz Khan2,3, Ling Shao2 1Tianjin University 2Inception Institute of Artificial Intelligence, UAE 3CVL, Linko¨ping University,...
为了运算方便,可以将Attention操作计算为:h=Attention(q、K、 V)。q也可以是一个向量序列Q(对应机器翻译中输入多个单词),此时输出也是一个向量序列H。Attention通用标准公式为:$$H=Attention(Q,K,V)=\begin{bmatrix} Attention(q_{1},K,V)\ ...\ Attention(q_{m},K,V)\end{bmatrix}$$ 这里,Q、K...
Attention mechanisms are widely used on NLP tasks and show strong performance in modeling local/global dependencies. Directional self-attention network shows the competitive performance on various datasets, but it not considers the reverse information of a sentence. In this paper, we propose the Multi...
First, we introduce a novel mask-guided attention network that fits naturally into popular pedestrian detection pipelines. Our attention network emphasizes on visible pedestrian regions while suppressing the occluded ones by modulating full body features. Second, we propose the occlusion-sensitive hard ...
[论文][人脸识别]High-Accuracy RGB-D Face Recognition via Segmentation-Aware Face Depth Estimation and Mask-Guided Attention Network 背景: 研究背景:基于 RGB-D 的人脸识别基本上以 2D 人脸识别方法为主,将与 RGB 对齐的深度图作为一个通道送入 CNN 网络,RGB-D 一个优势是增加了人脸的空间形状信息。能够...
(3) a mask-guided attention (MA) model that includes the part-aware mask-guided attention network beyond the SA model. 设计了三组消融实验,使用AUC分数和ROC曲线进行对比。 (1)基线网络ResNet50 (2)在基线网络增加soft attention (SA) model (3)在(2)的基础上增加mask-guided attention (MA) model...
Why will Mask Network fail and drop in price?Crypto projects fail for various reasons. Some of the most common ones are: team goes rogue and abandons the project, regulators declare it illegal and press exchanges to delist it, lack of media attention, more successful competitors, lack of ...
Mask-Guided Attention Network for Occluded Pedestrian Detection. (ICCV'19) - Leotju/MGAN
设计MaskBlock模块的主要目的是克服简单的MLP网络无法有效捕捉复杂交叉特征的局限性, 在这里也使用到了关键的attention机制[4],该模块主要包含三个组成部分: LayerNorm(层归一化)、instance-guided mask、feed-forward hidden layer(前馈隐藏层,获取重要的特征交互)。分别形成MaskBlock on Feature Embedding结构和MaskBlock...
模型中使用的简单channel attention模块与MobileNet Block中使用的是相同的。DWConv指的是深度可分离卷积,Point Conv指的是点卷积。在2(c)中,该模块包括四个点卷积。第一和第三个点卷积将输入通道的数量加倍,而第二和第四个点卷积保持相同的通道数量。门控机制将通道数量减半。