Efficient Pyramid Multi-Scale Channel Attention Modules: To capture the fine-grained multi-scale local feature and establish the long-term dependencies between channels, an efficient pyramid-type multi-scale channel attention (EPMCA) module is proposed, as shown in Fig. 5. It first extracts the ...
两种进一步创新的结构:KP-Pyramid 、RandLA-Pyramid Conclusion Abstract 背景 点云分割的最新进展主要是由局部聚合算子和点采样方法的新设计推动的。而与图像分割不同,很少有研究去理解尺度的基本问题以及尺度如何相互作用和融合。 创新 (1)论文研究了如何在点云分割网络中高效且有效地集成不同规模和不同阶段的特征。
Feature pyramidAttention moduleWith the development of deep learning, object detection has made substantial progress. However, when the object to be detected in the image is small or partially occluded, the detection network often fails to detect it successfully. We propose a multi-scale feature ...
Then, the result is combined with the features of the MS image as the input of the encoder, and these composite features are input to the pyramid attention mechanism module to capture multi-scale corresponding features. Next, the result of the input pyramid branch is input to the feature ...
[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...
In summary, our contributions are (1) introduction of a multi-scale pyramid of 3D FCNs; (2) improved segmentation of fine structures at higher resolution; (3) end-to-end training of multi-scale pyramid FCNs showing improved performance and good learning properties. We perform a comprehensive ev...
while maintaining multi-scale fields-of-view comparable to spatial pyramid configurations. Our results on multiple datasets demonstrate that OmniPose, with an improved HRNet backbone and waterfall module, is a robust and efficient architecture for multi-person pose estimation with state-of-the-art resu...
尽管这些使用特征金子塔的目标检测器具有很好的结果,但是由于仅仅根据固有的多尺度(为目标分类任务而设计的骨干的金字塔结构)。最新的,在这个工作中,作者提出了一个方法称为多级金字塔网络(Multi-Level Feature Pyramid Network, MLFPN)来构建检测不同尺度目标更有效的金子塔。
In order to exploit the multi-scale information of cascaded features more efficiently, the Multi-Scale Channel Adaptive Fusion module is embedded in the decoder. In addition, the Pyramid Feature Fusion module is introduced to realize the interaction of multi-level feature information, thus enhancing ...
11.1. The lower frequency subbands are smoother, and thus can be subsampled to allow a more efficient representation, generally known as a multiscale pyramid [1, 2]. The resulting collection of frequency subbands contains the exact same information as the input image, but, as we shall see,...