A multi-scale feature fusion block combined with context information, a convolutional neural network comprising a multi-scale feature fusion block combined with context information, a person re-identification method and apparatus based on the convolutional neural network, a device, and a storage medium...
First, a weight-based feature fusion block is designed to adaptively fuse information from several multi-scale feature maps. The feature fusion block can exploit contextual information for feature maps with large resolutions. Then, a context attention block is applied to reinforce the local region ...
3 CFENet CFENet在原始SSD上添加了4个CFE模块和2个Feature Fusion Block(FFB)模块,如图3所示。 图3 CEFNet网络结构 CFE模块的设计是为了增强SSD检测小目标的浅层特性,它的灵感来自于Inception,Xception,Large separable和ResNeXt等模块。 图4 CFE module示意图 CFE模块由两个相似的分支组成,左支使用 kxk Conv连接 ...
Last commit date Latest commit History 17 Commits data layers models utils .gitignore LICENSE README.md coco_voc.txt demo.py make.sh train_test_mob.py train_test_vgg.py README MIT license FFBNet FFBNET : LIGHTWEIGHT BACKBONE FOR OBJECT DETECTION BASED FEATURE FUSION BLOCK ...
该部分开发了两个更新和融合块(UAF Block)来渐进地改进融合特征Ffusion。 第i个UAF区块的架构 在每个UAF块中,雾霾特征和参考特征都由上一个融合特征更新,并进一步聚合得到改进的融合特征。 图像复原模块 利用融合后的特征Ffusion,本文发展了一个深度CNN模型Nd来估计W(x): ...
Table 2.Structures used in the feature fusion process and the results after use. Empty CellApplied structureTaskEffectReference Early fusionResidual blockDefective orange detectionImproved the classification accuracy(Chen et al., 2021c) Weed segmentationSolved degradation problem(Das and Bais, 2021) ...
Then, we integrate multiscale feature fusion (MSFF) block into the encoders which helps the network to learn multiscale features efficiently and enrich the information carried with skip connection and lower-resolution decoder by fusing contextual channel attention (CCA) models. Finally, in order to...
C.M.Sheela Rani, P.S.V.Srinivasa Rao, V.VijayaKumar, "Improved Block based Feature level Image fusion technique using Contourlet transform with Neural network", Signal & Image Processing : An International Journal (SIPIJ), 203-214, Vol.3, No.4, August 2012....
在FPN中,multi-scale feature fusion的作用远不如divide-and-conquer重要,因此multi-scale feature fusion可能不是FPN中最重要的benefit(ExFuse也描述了这一点)。进一步想,divide-and-conquer其实与OD中的optimization problem有关,它根据object scale将整个detection problem分成几个sub-problem,简化了optimization process ...
本文的组架构将B Basic Block结构与跳跃连接模块相结合。连续的B块增加了FFA - Net的深度和表现力。而跳跃连接使得FFA - Net绕过训练难点。在FFA - Net的最后,本文使用两层卷积网络实现和长捷径全局残差学习模块添加了恢复部分。 Feature Fusion Attention ...