1)Cross-modal Consensus Module 两个模态涵盖的是不同角度的特征信息,因此可以使他们相互做为辅助信息去检测另外一个模态中的冗余。CCM模型类似于self-attention中的Q、K、V形式。global-context-aware unit在时间轴上做池化,生成全局描述符MG∈RD(相当于Q);cross-modal-aware unit生成局部描述符ML∈R(T×D)(相...
CMX(Cross-Modal Fusion for RGB-X Semantic Segmentation with Transformers)是一种利用Transformer模型实现跨模态融合的方法,旨在提高RGB-X(其中X代表其他模态数据,如深度图、红外图像等)语义分割任务的性能。CMX通过融合来自不同模态的信息,使模型能够更全面地理解场景,从而提升分割的准确性和鲁棒性。 2. 阐述cross-...
Feature fusion 在获得每一层的特征映射后,我们构建了一个两阶段的特征融合模块(feature Fusion Module, FFM)来增强信息交互,并将两种模式的特征合并成一个单一的特征映射。如上图所示,在阶段1,两个分支仍然保持,并设计了交叉注意机制,在两个分支之间进行全局信息交换。然后,将这两个分支的输出连接起来。在第二阶段...
CMX的主要方框架如下图所示,使用两个并行主干从RGB和X模态输入中提取特征,中间输入 CM-FRM (cross-modal feature rectification module)进行特征修正,修正后的特征继续传入下一层。此外,同一层的特征还被输入FFM(feature fusion module)融合。下面将仔细介绍 CM-FRM 和 FFM。 CM-FRM: cross-modal feature rectificat...
The first three layers of bottom features are guided by advanced semantic features before and after fusion, to complete the repair of the lowlevel features. Finally, the final salient map is obtained. The proposed cross-modal feature fusion module can adaptively ...
In LoGFusion, we design the cross stage partial module with partial convolution (CSPMPC) to reduce feature redundancy and utilize the local cross-modal fusion module (LoCFM) and global cross-modal fusion module (GCFM) to capture both local and global cross-modal features. Furthermore, we ...
Notably, all of the four baselines are mainly used to implement the cross-modality fusion module g(Q, V)g(Q, V) of our robust VideoQA framework under the learning objective expressed in (6). The four baselines share the same input of video features (i.e., appearance and motion and qu...
A cross-modal fusion module is developed to learn the cross-modality correlations. An attention mechanism with an attention guidance module is implemented to help effectively and interpretably aggregate the aligned unimodal representations and the cross-modality correlations. Finally, we evaluate the ...
In this paper, for the RGB-D semantic segmentation task, we propose a novel cross-modal attention fusion network based on a universal vision transformer that fusion RGB and depth cross-modal features. We create the coordinate attention feature interaction module (CA-FIM) and the gated cross-atte...
CMX的主要方框架如下图所示,使用两个并行主干从RGB和X模态输入中提取特征,中间输入 CM-FRM (cross-modal feature rectification module)进行特征修正,修正后的特征继续传入下一层。此外,同一层的特征还被输入FFM(feature fusion module)融合。下面将仔细介绍 CM-FRM 和 FFM。 CM-FRM: cross-modal feature rectificat...