This paper proposes a lightweight multi-scale feature pyramid structure, which extracts features from network layers of different scales and aggregates them to supplement spatial detail information. Meanwhile, this paper adopts a pair of complementary attention modules, which pay attention to the ...
两种进一步创新的结构:KP-Pyramid 、RandLA-Pyramid 这一个模块就是为了掩饰提出的金字塔结构的encoder-decoder架构是通用的,故将其用在了另外两个网络中,并达到了好的效果。 Conclusion 论文提出了一种三向金字塔架构来处理和融合多尺度信息以进行点云分割。 论文使用了几个简单但有效的组件改进了常用的encoder-decoder...
they still have some shortcomings. On the one hand, as mentioned in the paper33, in the pyramid feature fusion structure, the deep feature information is transferred to the shallow features layer by layer. Therefore, the proportion of feature information carried by deep features ...
Title: PSConv: Squeezing Feature Pyramid into One Compact Poly-Scale Convolutional Layer 作者:Duo Li, Anbang Yao, and Qifeng Chen 发表单位:The Hong Kong University of Science and Technology;Intel Labs China 发表于:ECCV 2020 关键词:卷积核,多尺度 一句话总结:在卷积核内部设计多尺度信息提取。对...
Multi-scale text detectionGrouped pyramid moduleEfficient and effectiveScene text detection has attracted many researches due to its importance to various applications. However, current approaches could not keep a good balance between accuracy and speed, i.e., a high-performance accuracy but with a ...
Therefore, a multi-scale feature fusion pyramid attention network (PAN) for single image dehazing is proposed. In PAN, combined with the attention mechanism, a shallow and deep feature fusion (SDF) strategy is designed. SDF considers multi-scale as well as channel-level fusion to provide ...
the concept of a feature pyramid was introduced. Methods such as FPN24, PANet25, two-way FPN26, etc. enhance model performance by fusing features of different scales through top-down or bottom-up pathways. EfficientDet49introduces a repeatable BiFPN for iterative feature fusion, further enhancing...
[ECCV 2020] PSConv: Squeezing Feature Pyramid into One Compact Poly-Scale Convolutional Layer pytorchconvolutionobject-detectioninstance-segmentationmulti-scalemmdetectionfeature-pyramidseccv2020 UpdatedJul 14, 2020 Python Multi-Scale Continuous CRFs as Sequential Deep Networks for Monocular Depth Estimation in...
浅层可以在高空间分辨率下用小的channel维度建立简单的low-level feature,而深层则可以用更大的channel维度建立更high-level的语义信息,这个是特征金字塔的思想。 Multi Head Pooling Attention:相比于MHA加入了pooling操作,主要作用是改变token个数。其中cls token没有参与pooling操作。
提出了金字塔卷积pyramidal convolution (PyConv);包括a pyramid of kernels;每个分支都拥有不同尺寸和深度的filters; 计算方面,与标准卷积计算量相同; 1. Method pyramidal convolution (PyConv): 平行的多个卷积核; 从上至下:卷积核size逐渐变小,卷积核depth逐渐变大。因为size大了参数多,这样设计也是为了计算效率;...