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Hierarchical multiples self-attention mechanism for multi-modal analysis
Because of the massive multimedia in daily life, people perceive the world by concurrently processing and fusing multi-modalities with...
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Multi-modal fusion learning through biosignal, audio, and visual content for detection of mental stress
Mental stress is a significant risk factor for several maladies and can negatively impact a person’s quality of life, including their work and...
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TMIF: transformer-based multi-modal interactive fusion for automatic rumor detection
The rapid development of social media platforms has made them one of the most important news sources. While it provides people with convenient...
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Video Rumor Classification Based on Multi-modal Theme and Keyframe Fusion
In recent years, short video platforms have become the main source of online rumors. According to the statistics of Shanghai online rumor refutation...
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Multi-Modal Generative DeepFake Detection via Visual-Language Pretraining with Gate Fusion for Cognitive Computation
With the widespread adoption of deep learning, there has been a notable increase in the prevalence of multimodal deepfake content. These deepfakes...
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Dictionary-Induced Manifold Learning for Incomplete Multi-modal Fusion
Data missing is a common problem in multi-modal fusion, and existing incomplete multi-modal methods usually only consider the case of two modalities...
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Label graph learning for multi-label image recognition with cross-modal fusion
It has become popular to learn the correlation between labels in most existing multi-label image recognition tasks. Existing approaches begin to...
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Multi-grained encoding and joint embedding space fusion for video and text cross-modal retrieval
Video-text cross-modal retrieval is significant to computer vision. Most of existing works focus on exploring the global similarity between...
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MutualFormer: Multi-modal Representation Learning via Cross-Diffusion Attention
Aggregating multi-modal data to obtain reliable data representation attracts more and more attention. Recent studies demonstrate that Transformer...
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EnCoSum: enhanced semantic features for multi-scale multi-modal source code summarization
Code summarization aims to generate concise natural language descriptions for a piece of code, which can help developers comprehend the source code....
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MLF-DET: Multi-Level Fusion for Cross-Modal 3D Object Detection
In this paper, we propose a novel and effective Multi-Level Fusion network, named as MLF-DET, for high-performance cross-modal 3D object DETection,...
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3D reconstruction-oriented fully automatic multi-modal tumor segmentation by dual attention-guided VNet
Existing automatic contouring methods for primary nasopharyngeal carcinoma (NPC) and metastatic lymph nodes (MLNs) may suffer from low segmentation...
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Deep adversarial multi-label cross-modal hashing algorithm
In recent years, more and more researchers employ the hashing algorithm to improve the large-scale cross-modal retrieval efficiency by map** the...
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CMC-MMR: multi-modal recommendation model with cross-modal correction
Multi-modal recommendation using multi-modal features (e.g., image and text features) has received significant attention and has been shown to have...
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Homogeneous Multi-modal Feature Fusion and Interaction for 3D Object Detection
Multi-modal 3D object detection has been an active research topic in autonomous driving. Nevertheless, it is non-trivial to explore the cross-modal...
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Gated Multi-modal Fusion with Cross-modal Contrastive Learning for Video Question Answering
Video Question Answering (VideoQA) is a challenging task that requires the model to understand the complex nature of video data and the variety of...
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The effectiveness of children’s English enlightenment network teaching based on multi-modal teaching model
To enhance the efficacy of traditional English enlightenment education for children, this research delves into a multi-modal teaching approach and...
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Multi-Modal 3D Object Detection in Autonomous Driving: A Survey
The past decade has witnessed the rapid development of autonomous driving systems. However, it remains a daunting task to achieve full autonomy,...
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Multi-modal Depression Estimation Based on Sub-attentional Fusion
Failure to timely diagnose and effectively treat depression leads to over 280 million people suffering from this psychological disorder worldwide....
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Multi-modal medical image fusion based on densely-connected high-resolution CNN and hybrid transformer
Multi-modal medical image fusion (MMIF) has found wide application in the field of disease diagnosis and surgical guidance. Despite the popularity of...
