DSHDA, we propose a deep neural network to simultaneously integrate feature and hash code learning for each modality into the same framework, the training of the framework is guided by the label semantic features and hash codes generated from SeLabNet to maximize the cross-modal semantic relevance...
motivation:对跨模态和多模态的一种结合。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...
Cross-modal retrieval(CMR) aims to retrieve the instances of a specific modality that are relevant to a given query from another modality, which has drawn ... JI Zhong,K Chen,HE Yuqing,... - 《Science China Information Sciences》 被引量: 0发表: 2022年 DMRM: A Dual-channel Multi-hop ...
Cross-Visual Attention Fusion Network with Dual-Constrained Marginal-Ranking for Visible-Infrared Person Re-Identification Visible-Infrared Person re-identification(VI-REID) is extremely important for night-time surveillance applications. It is a challenging problem due to large cross-modality discrepancies ...
This paper focuses on exploring internal dependencies and the cross-modal correlation between the image and question sentence for visual question answering (VQA). Specifically, we propose a novel VQA model, i.e., Dual Self-Attention with Co-Attention networks (DSACA). The framework of DSACA mai...
Lin, J.et al.CKD-TransBTS: Clinical knowledge-driven hybrid transformer with modality-correlated cross-attention for brain tumor segmentation.ITMI2451–2461 (2023). Yan, X.et al.After-unet: Axial fusion transformer unet for medical image segmentation. InProceedings of the IEEE/CVF Winter Conference...
Attention-driven dynamic graph convolutional net- work for multi-label image recognition. In European Con- ference on Computer Vision, pages 649–665. Springer, 2020. 2, 6, 7 [42] Renchun You, Zhiyao Guo, Lei Cui, Xiang Long, Yingze Bao, and Shilei Wen...
(CBF) in the prefrontal cortex and medial/posterior cingulate cortex. On the contrary, physical training has been associated with improved memory, correlating with an increase in CBF in the hippocampus. These findings corroborate the premise that each training modality uniquely contributes to ...
highlights its own spectral features. Similarly, a "cross-attention" approach is simultaneously used to harness the LiDAR derived attention map that accentuates the spatial features of HSI. These attentive spectral and spatial representations are then explored further along with the original data to ...
To enhance robustness against noisy samples, we introduce cross-modality graph structured attention to reinforce the representation with the contextual relations across the two modalities. We also develop a parameter-free dynamic dual aggregation learning strategy to adaptively integrate the two components ...