(2)在Self-Attention模块内部,部分方法放弃了K和V的部分表达,相邻嵌入的键/值经常被合并,以降低成本。因此,即使嵌入同时具有小尺度和大尺度特征,合并操作也会丢失每个单个嵌入的小尺度(细粒度)特征,从而使跨尺度注意力失效。例如,Swin-Transformer将self-attention操作的范围限制在每个window内,这一定程度上放弃了全局...
为了解决上述问题,作者提出了Cross-scale Embedding Layer(CEL) 和Long Short Distance Attention(LSDA) 两个模块。其中 CEL 模块将不同尺度的特征进行融合,为 self-attention 模块提供了跨尺度的特征;LSDA 模块将 selff-attention 模块分为 short-distance 和 long-distance 两个部分,不仅减少了计算的负担,还保留了...
这里要先遍历embed_w即V特征,值得注意的是步长设置为self.stride*self.scale即3 * 3=9,只是因为后续还要对降采样后的影像进行unfold,所以为了生成相同数量的patch,步长要设置为‘self.stride’的‘self.scale’倍,而后面降采样影像步长为self.stride就可以保证生成相同数量的patch(为什么要生成相同数量的patch后面分析...
scale, so no cross-scale feature can be extracted; (2) to lower the computational cost, some vision transformers merge adjacent embeddings inside the self-attention module, thus sacrificing small-scale (fine-grained) features of the embeddings and also disabling the cross-scale interactions. To ...
CrossFormer: A Versatile Vision Transformer Hinging on Cross-scale Attention https://arxiv.org/abs/2108.00154 https://github.com/cheerss/CrossFormer 这是视觉的Transformer 演进过程:VIT---PVT---CrossFormer VIT没有考虑多尺度信息 PVT通过特征下采样集成了多尺度信息...
CrossFormer:A Versatile vision transformer Based on cross-scale attention (一种基于跨尺度注意力的多功能视觉transformer) (浙江大学、哥伦比亚大学、腾讯数据平台) Abstract Transformers在处理视觉任务方面取得了很大进展。然而,现有的vision transformer仍然不具备一种对视觉输入很... ...
In this paper, we propose a cross-scale attention\n(CSA) model, which explicitly integrates features from different scales to form\nthe final representation. Moreover, we propose the adoption of the attention\nmechanism to specify the weights of local and global features based on the\nspatial ...
attention = torch.matmul(Q, K.permute(0, 1, 3, 2)) / self.scale #把 mask 不为空,那么就把 mask 为 0 的位置的 attention 分数设置为 -1e10 if mask is not None: attention = attention.masked_fill(mask == 0, -1e10) #第 2 步:计算上一步结果的 softmax,再经过 dropout,得到 attent...
crossattention模块出来是权重吗 cross-modal 1.跨模态检索的定义 在这篇文章中A Comprehensive Survey on Cross-modal Retrieval,作者给出了跨模态检索(Cross Modal Retrieval)的定义:It takes one type of data as the query to retrieve relevant data of another type。大概意思就是说,将一种类型的数据作为查询...
In particular, CEL blends each embedding with multiple patches of different scales, providing the model with cross-scale embeddings. LSDA splits the self-attention module into a short-distance and long-distance one, also lowering the cost but keeping both small-scale and large-scale features in ...