2、Gated fusion sub-network 该子网络主要是融合了不同层次的特征信息,以往的网络都是直接添加short-cut操作进行信息融合,本文的Gate fusion network 为不同层次的特征分别学习了权重,最后加权得到融合的特征层。 3、network 这篇文章的网络很简单,可以看做简单的三个部分:encoder,feature transfer,decoder.其中feature...
论文阅读: Gated Context Aggregation Network for Image Dehazing and Deraining,程序员大本营,技术文章内容聚合第一站。
如[10,9]所示,除了输入图像之外,预先计算输入图像的边缘并将它们作为辅助信息馈送到网络中对网络学习非常有帮助。 因此,默认情况下,我们也采用这个简单的想法,并将预先计算的边缘与沿着通道维度的输入模糊图像连接起来作为GCANet的最终输入。 损失函数在先前基于学习的图像去雾方法[3,31,22,24,42,44]中,采用简单的...
Gated Context Aggregation Network for Image Dehazing and Derainingdoi:10.1109/WACV.2019.00151Dongdong ChenMingming HeQingnan FanJing LiaoLiheng ZhangDongdong HouLu YuanGang HuaIEEEWorkshop on Applications of Computer Vision
In this paper, we propose a new end-to-end gated context aggregation network GCANet for image dehazing, in which the smoothed dilated convolution is used to avoid the gridding artifacts and a gated subnetwork is applied to fuse the features of different levels. Experiments show that GCANet can...
Context Aggregation 除了局部特征之外,高级语义上下文建模对于视觉识别也是至关重要的。经典ConvNets通常使用这些模块的深层堆栈来捕获受其接受域限制的长距离交互。然而,这些设计可能在计算上效率低下,并产生冗余特征。为了解决这一难题,提出了上下文聚合模块,以自适应地探索和强调潜在的上下文信息,并减少输入特征中的冗余...
(2019). Gated context aggregation network for image dehazing and deraining. In IEEE winter conference on applications of computer vision (pp. 1375–1383). IEEE. Cho, S., & Lee, S. (2009). Fast motion deblurring. ACM Transactions on Graphics, 28(5), 145. Article Google Scholar Dong, ...
论文笔记:A Gated Self-attention Memory Network for Answer Selection,程序员大本营,技术文章内容聚合第一站。
Inspired by recent research on dilated convolutions for context aggregation, we propose a novel convolutional neural network (CNN) to deal with noise- and speaker-independent speech separation. The proposed model incorporates dilated convolutions, gating mechanisms and residual learning. We find that ...
Abstract: 研究上下文语义的依赖性为得到精准的分割结果,但大多数研究都是区分不同types的语义依赖性,这会损失scene understanding。 本文设计了Context Prior Network(CPNet)主要是用于区分intra-class和inter-class,提升语义依赖性。CPNet是在backbone上添加CP Layers with Affinity Loss。... ...