目前单视角COD方法对背景干扰很敏感,难以检测到模糊的边界和可变形状的伪装对象。为了克服这些障碍,论文提出了一个基于行为的框架,称为多视角特征融合网络(Multi-view Feature Fusion Network, MFFN)。该框架模拟了人类在图像中寻找模糊物体的行为,即从多个角度、距离、视角进行观察。它背后的关键思想是通过数据增强生成...
including two sub-networks: a Temporal Alignment Network (TAN) fTAN and a Modulative Feature Fusion Network (MFFN) fMFFN . fTAN 接受参考框架 ILRt 和一个支撑框架 ILRt+i 作为输入,并将对应支撑框架的对齐特征 F~t+i 估计为,,然后,支撑框架的所有对齐特征连接为 受[33] 中的空间特征变换 (SFT—...
模型浅析 为了共同学习特征融合和图融合,本文提出了一个端到端统一的神经网络框架,由两个主要组件组成:特征融合网络(Feature Fusion Network)和可学习的GCN(Learnable Graph Convolutional Network)。 Feature Fusion Network 将原始多视图表示映射到共享的隐藏空间。这里使用稀疏自编码器来探索所有视图的过完备的潜在表示。
learn the semantic correlation between data. Then, a multi-scale feature fusion module is trained to adaptively fuse the contextual information at multiple scale, thus capturing multi-scale object information. To the end, the proposed FFNet experiments conducted on the PASCAL-5iand COCO-20idatasets ...
(3)Feature Fusion Network(FFN): 特征融合单元包含两个步骤:① 特征的计算和选择,采用元素最大策略(理解是三个区域的特征向量每个元素都选值最大的那个,如下图所示);② 特征的转换,采用内积计算(理解是对全局、区域特征融合时候采用了内积,将两个256维向量融合为一个256维向量)。
本文提出了一个轻量化的CNN-Transformer Feature Fusion Network(HCT-FFN),其可以在各阶段协调transformer和CNN,利用他们自身的优势。(第一个阶段和最后一个阶段是cnn stage,别的阶段是transformer stage) 具体来说,在CNN-stage,本文堆叠了degradation-aware mixture of experts (DaMoE) module,其作用是在适当的情况...
To address this issue, this paper presents a multi-scale feature fusion network (MSFFNet) based on CNN (convolution neural network), which is capable of detecting enough semantic features to understand crowds in sparse and highly congested scenes. In this method, a large majority of encoded ...
In this paper, we propose an end-to-end trainable architecture called Coordinated Feature Fusion Network (CFFNet) to tackle the aforementioned problems. The proposed model contains a powerful baseline network and embeds two primary modules: Spatial Alignment Module (SAM) and Semantic Consistency ...
Additionally, their network structures are relatively complex, resulting in poor detection speed. To achieve accurate pedestrian detection in complex scenes, we propose an efficient attention feature fusion network. Specifically, firstly, a dual-backbone network is designed to extract dual-modality ...
论文题目《Hyperspectral Image Classification With Deep Feature Fusion Network》 论文作者:Weiwei Song, Shutao Li, Leyuan Fang,Ting Lu 论文发表年份:2018 网络简称:DFFN 发表期刊:IEEE Transactions on Geoscience and Remote Sensing 一、本文提出的挑战 ...