Cross-Modality Attentive Feature Fusion for Object Detection in Multispectral Remote Sensing Imagery - rubbish-qi/CMAFF
Cross-modality fusing complementary information of multispectral remote sensing image pairs can improve the perception ability of detection algorithms, making them more robust and reliable for a wider range of applications, such as nighttime detection. Compared with prior methods, we think different featu...
Local featureHybrid weighted attentionTwo-stream networkCross-modal person re-identification between the visible (RGB) modality and infrared (IR) modality is extremely important for nighttime surveillance applications. In addition to the cross-modal differences caused by different camera spectra, RGB-IR ...
ZHANG Y Y, LI G R, CHU L Y, et al. Cross-media topic detection: a multi-modality fusion framework[C]//Proceed-ings of the 2013 IEEE International Conference on Multi-media and Expo, San Jose, Jul 15-19, 2013. Washington: IEEE Computer Society, 2013: 1-6.. ...
Xmodal[26](X Modality)是利用中间辅助模态X,将两种模态的问题转化为三模态问题。cm-SSFT[28](cross-modality Shared Specific Feature Transfer)实现了目前跨模态行人重识别的最高性能,该方法融合了模态共享特征和模态特定特征,可以基于最近邻传播来自不同模态的信息,但是该方法有复杂的网络结构,且需要辅助数据集,...
Attentive Intra-modality Fusion for Multimodal Sentiment Analysis Chapter © 2021 Multimodal Social Media Sentiment Analysis Based on Cross-Modal Hierarchical Attention Fusion Chapter © 2022 Explore related subjects Discover the latest articles, news and stories from top researchers in related subjec...
To download the pre-processed IEMOCAP dataset, use the link given inhttps://github.com/david-yoon/attentive-modality-hopping-for-SEROnce you have it downloaded, replace the 'data_path' in 'multi_run.sh' with your folder path. Note: The processed dataset repo from Dr. David Yoon contains,...
4.2. Implementation Details The proposed Multi-Modality Cross-Attention Network is implemented in PyTorch framework [27] with a NVIDIA GeForce GTX 2080Ti GPU. In the self-attention module, for the image branch, the image region feature vector extracted by a bot...
We explore semantics among the multimodal inputs in two aspects: the modality-shared consistency and the modality-specific variation. Specifically, we propose a novel network, termed XMSNet, consisting of (1) all-round attentive fusion (AF), (2) coarse-to-fine decoder (CFD), and (3) cross...
for these multi-modality features have been shown to generate highly accurate land-cover maps. However, fusion in the context of RS is non-trivial considering the redundancy involved in the data and the large domain differences among multiple modalities. In addition, the feature extraction modul...