不过,从名字上猜测,"stratified"通常与分层抽样有关,而"transformer"通常指的是一种深度学习架构。结合这两者,我猜测stratified_transformer可能是一个用于分层抽样的深度学习模型。 分层抽样是一种统计技术,用于在数据集中保留某些属性(或特征)的原始分布。这在处理不平衡数据集时特别有用,因为它可以帮助模型更好地学习...
代码开源在https:// github.com/ dvlab-research/ StratifiedTransformer 每个点云视为一个token,编码器中的第一个模块中,采用point embedding来聚合局部信息(KPConv),point embedding的引入有利于加速网络收敛。 借鉴Swin Transformer的patch划分方法,将点云划分成多个不重叠的立体窗口,为进一步的提高感受野,引入了一种...
Point Transformer[62]使用 "向量自我注意 "算子来聚集局部特征,并使用 "减法关系 "来生成注意权重,但它存在缺乏长程上下文和测试中各种扰动时不够稳健的问题。我们的工作是基于指向性的,并与Transformer密切相关,但有一个根本的区别:我们的工作克服了有限的有效感受场问题,并充分利用Transformer来模拟长距离的语境依赖...
Vanilla Version Transformer(未分层)缺陷:针对一个格子中的一个query点来讲,通过transformer对其进行特征提取时,所依赖的全局信息只有所在的格子中的所有点云,这就导致了Vanilla Version Transformer其感受域是非常有限的,以至于针对query很难提取到远距离的点与点之间的依赖,可能会导致预测时的错误。 StratifiedKey-sampli...
Stratified Transformeris point-based, and constructed by Transformer with standard multi-head self-attention, enjoying large receptive field, robust generalization ability as well as competitive performance; This repository develops a memory-efficient implementation to combat the issue ofvariant-length tokens...
While transformers have shown great potential on video recognition with their strong capability of capturing long-range dependencies, they often suffer high computational costs induced by the self-attention to the huge number of 3D tokens. In this paper, we present a new transformer architecture ...
现有方法:generative transformer主要以language-modeling style来处理视觉内容,其中image/video/其他结构化输入被处理为离散的token序列。这些内容由不同的层次构成,e.g.从子像素到边缘,这些层次在处理中被忽略了 创新点:本文利用图像的层次性将visual token encode为分层的(stratified levels) 优势:通过所提出的图像分层...
In this paper, we present a new transformer architecture termed DualFormer, which can efficiently perform space-time attention for video recognition. Concretely, DualFormer stratifies the full space-time attention into dual cascaded levels, i.e., to first learn fine-grained local interactions among...
In the conventional stacking method of the laminated core of a transformer, grain-oriented silicon steel sheet pieces of an identical grade or the identical magnetic properties are used as legs and yokes of the core. In a highly oriented silicon steel sheet having a high B8 value due to ...
In this paper, we present a Transformer-based parallel refinement network to improve the accuracy of coarse predictions and allow fine predictions to be adjusted, based on the accurate coarse positional information. Our proposed structure, called SMART, maximizes the utilization of coarse-level rich-...