Multi-scale receptive field is introduced in the new framework to extract multi-scale features, which can better represent defects than the feature maps produced by a single convolutional layer. A group of AutoEncoders are trained to reduce the dimension of the extracted multi-scale features which...
We aim to study the multi-scale receptive fields of a single convolutional neural network to detect faces of varied scales. This paper presents our Multi-Scale Receptive Field Face Detector (MSFD), which has superior performance on detecting faces at different scales and enjoys real-time inference...
The fTAN includes three modules: feature extraction module, Multi-scale Dilated Deformable (MDD) alignment module and attention module. 特征提取模块、多尺度扩张变形(MDD)对齐模块和注意力模块。 1)Feature Extraction Module: 特征提取模块: 由一个卷积层和 5 个带有 ReLU 激活函数的残差块[38] 组成。 使...
Besides, to solve the problem of reduced recognition accuracy caused by the inconsistent size and scale of the assembly tools in the assembly behavior image, this paper designs a multi-scale feature fusion method, which can recognize more accurate feature information between specific assembly behaviors...
能构建更深的网络,增大“receptive field” 模糊图像和清晰图像在数值上本身就比较相近,因此仅仅让网络学习两者的差异也够了 整体网络结构 文中选择了K=3的“multi-scale architecture”,输入、输出的“Gaussian pyramid patches”大小为{256×256,128×128,64×64}。 B_{k},L_{k},S_{k} 分别表示模糊图像、...
"Multi-scale image analysis based on non-classical receptive field mechanism". In Neural Information Processing (pp. 601-610). Springer Berlin Heidelberg.Wei, H., Zuo, Q., & Lang, B. (2011, January). "Multi- scale image analysis based on non-classical receptive field mechanism". In ...
代码地址:GitHub - dvlab-research/MSAD: Multi-Scale Aligned Distillation for Low-Resolution Detection (CVPR2021) 一、要解决的问题(Why) 这篇文章做的任务是目标检测。一般来说,降低图像分辨率可以显著提高目标检测的精度,但与此同时精度也会降低。本文的目标和 [CVPR2020]Dual Super-Resolution Learning for ...
针对语义分割问题 semantic segmentation,这里使用 dilated convolutions 得到multi-scale context 信息来提升分割效果。 dilated convolutions: 首先来看看膨胀卷积 dilated convolutions , 图(a):就是一个常规的 3*3 卷积,1-dilated convolution 得到 F1, F1的每个位置的 receptive field 是 3×3 图(b): 在 F1...
对于aspect ratio 为 1 时,本文还增加了一个 default box,这个 box 的 scale 是 s′k=sksk+1−−−−−√ 。所以最终,在每个 feature map location 上,有 6 个 default boxes。 每一个 default box 的中心,设置为: (i+0.5|fk|,j+0.5|fk|) ,其中, |fk| 是第 k 个feature map 的大小,...
Multiscale Object Detection 我们在输入图像的每个像素上生成多个锚框。这些定位框用于对输入图像的不同区域进行采样。但是,如果锚定框是以图像的每个像素为中心生成的,很快就会有太多的锚框供我们计算。例如,我们假设输入图像的高度和宽度分别为561和728像素。如果以每个像素为中心生成五个不同形状的锚框,则超过两百...