于是,作者提出来一种inductive bias:基于self-attention的方法在模型的shllow layer必须更关注于local dependencies,而在high layer中要平衡好local dependencies 与non-local dependencies之间的关系。基于这个inductive bias,作者提出了multi-scale multi-head self-attention (MSMSA)并以此构建了Multi-Scale Transformer。最...
## Scale Modulation Module (SAM)classScaleAwareModule(nn.Module):def__init__(self,in_dim,out_dim,num_heads,expand_ratio,shortcut=False,act_type='silu',norm_type='BN'):super().__init__()# --- Basic parameters ---self.in_dim=in_dimself.out_dim=out_dimself.num_heads=num_headsse...
Scale-aware attention network for weakly supervised semantic segmentation Multi-scale featureAttention mechanismWeakly supervised semantic segmentation (WSSS) using image-level labels greatly alleviates the burden of obtaining large ... Z Cao,Y Gao,J Zhang - 《Neurocomputing》 被引量: 0发表: 2022年...
Recent methods of scene text recognition usually focus on handling shape distortion, attention drift, or background noise, ignoring that text recognition encounters character scale-variation problem. To address this issue, in this paper, we propose a new scale-aware hierarchical attention network (...
Scale-Aware Attention Network for Crowd Counting 论文笔记 不同层的多尺度密度预测。为了将这些 maps 聚合到我们的最终预测中,我们提出了一种新的soft 注意力机制,其可以学习一组 gating masks。此外,我们引入了规模感知损失函数来规范不同分支的训练并指导它们专门研究特定的尺度。由于这种新训练需要对每个头部的大...
withoutbeingawareofwhatI'm doing. 11.Ifindmyselflisteningtosomeonewithoneear,doing somethingelseatthesametime. 12.Idriveplaceson"automaticpilot"andthenwonderwhyIwent there. 13.Ifindmyselfpreoccupiedwiththefutureorthepast. 14.Ifindmyselfdoingthingswithoutpayingattention. 15.IsnackwithoutbeingawarethatI'm...
Clinicians should use both informant- and self-report rating scales to gather as much information as possible, while being aware that informants are subject to rater error and adolescents typically underreport symptoms. Rating scales can establish a baseline measure of the patient's symptom type and...
MSA-Net Multi-Scale Attention Network for Crowd Counting 2019 作者:亚马逊 论文:https://arxiv.org/abs/1901.06026 创新点: 在backbone中就产生了多尺度的density map,经过上采样后,加入软注意力机制进行加权叠加。 提出了一个scale-aware loss,但是实验结果好像表明效果不大。... ...
多头混合卷积Multi-head Mixed Convolution(MHMC)和尺度感知聚合Scale-aware Aggregation(SAA) 此外,文中还提出了一种进化混合网络Evolutionary Hybrid Network(EHN),为CNN和transformer的混合网络。 这篇文章提出了两个主要动机: 一个动机是,构建Vision Transformer(ViT)框架时,使用的Self-attention(SA)具有O(N2)方的计...
Attention to Scale: Scale-aware Semantic Image Segmentation(attention部分) 真不知道叫什么 2 人赞同了该文章 多尺度输入被应用于共享网络进行预测。在这项工作中,我们证明了共享网络在与注意机制相结合的情况下,在规模上的有效性。 基于共享网络,假设一个输入图像被调整到几个尺度s∈{1,...,S}。每个尺度都...