In order to better combine the two modalities, we propose a novel Cross-Modal Transformer for human action recognition鈥擟MF-Transformer, which effectively fuses two different modalities. In spatio-temporal modality, video frames are used as inputs and directional attention is used in the ...
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-...
论文解读——CMT:Cross Modal Transformer 论文解读——CMT:Cross Modal Transformer CMT 是旷视在 ICCV2023 的一篇论文,其基于 PERT,并加入了激光雷达数据,利用 Transformer 很好地融合了两种模态的数据。新手小白建议先看 DETR 系列。论文的继承关系为:CMT -> PETR -> DETR3D -> Deformable DETR -> DETR。可以...
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...
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...
图3. Cross-Modal Transformer (CMT) 范例的架构。多视图图像和点云被输入到两个骨干网络以提取特征标记。在坐标编码模块中,相机光线和BEV位置的坐标分别转换为图像位置编码(Im PE)和点云位置编码(PC PE)。查询由位置引导查询生成器生成。在查询生成器中,3D 锚点被投影到不同的模态,并且相对坐标被编码(参见右侧...
However, existing fusion algorithms may not achieve encouraging performance owing to the enormous difference between the two modalities. In this work, we propose a Transformer-based cross-modal information fusion network (TCIFNet) scheme to explore model discrepancies. To this end, we first project ...
Cross Modal Transformer: Towards Fast and Robust 3D Object Detection Junjie Yan Yingfei Liu ✉ Jianjian Sun Fan Jia Tiancai Wang Xiangyu Zhang MEGVII Technology Shuailin Li Abstract In this paper, we propose a robust 3D detector, named Cross Modal Transformer (...
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...
论文地址:CMX: Cross-Modal Fusion for RGB-X Semantic Segmentation with Transformers 代码地址:https://github.com/huaaaliu/RGBX_Semantic_Segmentation 本文贡献: 提出了CMX,一种基于vison-transformer的跨模态融合框架,用于RGB-X语义分割(X为RGB的互补模态); ...