和现有的使用多模态transformer encoder[multimodal]进行visual tokens和word tokens联合建模不同,这篇工作对图片和文本分别使用Transformer提取特征[unimodal]之后使用对比损失进行对齐,然后进行cross-modal attention。为了克服数据中的噪声带来的不利影响,使用动量模型生成的伪标签进行训练。 传统的多模态VLP方法的limitations:...
Cross-modality interactive attention network for multispectral pedestrian detection Inf. Fusion (2019) C.Liet al. Illumination-aware faster R-CNN for robust multispectral pedestrian detection Pattern Recogn. (2019) Y.Xueet al. MAF-YOLO: Multi-modal attention fusion based YOLO for pedestrian detection...
To address these issues, firstly, we propose a cross-modality dual attention fusion module (CMDA) equipped with spatial–temporal and channel-wise attention mechanisms to explicitly transfer information not only from the Fast pathway to Slow as in SlowFast, but also from Slow to Fast. Fig. 1(...
(2022). Dual-Branch Squeeze-Fusion-Excitation Module for Cross-Modality Registration of Cardiac SPECT and CT. In: Wang, L., Dou, Q., Fletcher, P.T., Speidel, S., Li, S. (eds) Medical Image Computing and Computer Assisted Intervention – MICCAI 2022. MICCAI 2022. Lecture Notes in Comp...
cross-attention from the prompt (as a query) directed to the embedded image. In contrast, prompt featuresBcare obtained through cross-attention from the embedded image (as a query) directed to the prompts. These two cross-attention mechanisms facilitate the learning of the dependencies between ...
(CDDFuse) network. Firstly, CDDFuse uses Restormer blocks to extract cross-modality shallow features. We then introduce a dual-branch Transformer-CNN feature extractor with Lite Transformer (LT) blocks leveraging long-range attention to handle low-frequency global features and Invertible Neural ...
19ArXiv之ReID:Enhancing the Discriminative Feature Learning for Visible-Thermal Cross-Modality Person training D2RL:Learningtoreducedual-leveldiscrepancyforinfrared-visiblepersonre-identification...two-stream structure 同Hierarchical DiscriminativeLearningforVisibleThermalPersonRe-Identification文章的双流结构相似具体...
text cross-modal retrieval is shown in Fig. 1. Video vs. text cross-modal retrieval methods are mainly divided into two categories: the retrieval method based on video single modality feature [14] and the retrieval method based on video multi-modal feature [15], [16]. Among them, the ...
Bases on the self-attention mechanism, the Dual Self-Attention with Co-Attention networks (DSACA) are proposed to capture the internal dependencies and cross-modal correlation between the image and question sentence. • Extensive experiments performed on three public VQA datasets confirm the favorable...
most existing methods directly fuse attentional cross-modality features under a manual-mandatory fusion paradigm without considering the inherent discrepancy between the RGB and depth, which may lead to a reduction in performance. Moreover, the long-range dependencies derived from global and local inform...