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Rethinking the role of attention mechanism: a causality perspective
As the core technology of Transformers, the attention mechanism is almost indispensable. However, many experimental findings show that the models...
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Deep Triply Attention Network for RGBT Tracking
RGB-Thermal (RGBT) tracking has gained significant attention in the field of computer vision due to its wide range of applications in video...
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TULAM: trajectory-user linking via attention mechanism
Recently, the application of location-based services (LBS) has become a prevalent means to provide convenience in customers’ everyday lives. However,...
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Text-assisted attention-based cross-modal hashing
As one of the hottest research topics in multimedia information retrieval, cross-modal hashing has drawn widespread attention in the past decades....
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Image manipulation localization using reconstruction attention
With the development of image manipulation techniques and the widespread use of image editing tools, it is effortless to forge images without leaving...
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Modified dual attention triplet-supervised hashing network for image retrieval
In view of the problems of insufficient feature extraction and ineffective capture of correlation between deep features in existing image retrieval...
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Deep Bharatanatyam pose recognition: a wavelet multi head progressive attention
Human pose identification from 2D video sequences is extremely challenging under the influence of recording artifacts such as lighting, sensor...
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Class attention network for image recognition
Visual attention has become a popular and widely used component for image recognition. Although various attention-based methods have been proposed...
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CANet: cross attention network for food image segmentation
Food image segmentation which aims to distinguish various ingredients is crucial for food safety, as estimating calories and other nutrients is...
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Towards Robust Semantic Segmentation against Patch-Based Attack via Attention Refinement
The attention mechanism has been proven effective on various visual tasks in recent years. In the semantic segmentation task, the attention mechanism...
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Predicting human poses via recurrent attention network
Human motion prediction is a challenging task due to the diversity and randomness of future poses. Due to the inherent topology of pose data, most...
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Image color rendering based on frequency channel attention GAN
In recent years, channel attention mechanism has greatly improved the performance of computer vision-oriented network models. But the simple...
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Lightweight dynamic attention network for single thermal image super-resolution
The embedding of attention mechanism in convolutional neural networks (CNN) effectively improves the performance of single image...
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Joint self-attention for denoising Monte Carlo rendering
Image-space denoising of rendered images has become a commonly adopted approach since this post-rendering process often drastically reduces required...
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Attention with kernels for EEG-based emotion classification
A kernel attention module (KAM) is presented for the task of EEG-based emotion classification using neural network based models. In this study, it is...
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SAEFormer: stepwise attention emphasis transformer for polyp segmentation
Polyp segmentation in colorectal images is the most effective and necessary tool for the early detection of colorectal cancer, and deep learning has...
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Masked co-attention model for audio-visual event localization
The objective of Audio-Visual Event Localization (AVEL) is to leverage audio and video cues in a combined manner to localize video segments that...
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Scene Text Detection Using HRNet and Spatial Attention Mechanism
AbstractTo better extract the features from text instances with various shapes, a scene text detector using High Resolution Net (HRNet) and spatial...
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Weakly supervised target detection based on spatial attention
Due to the lack of annotations in target bounding boxes, most methods for weakly supervised target detection transform the problem of object...
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DAF-Net: dense attention feature pyramid network for multiscale object detection
In recent years, object detection has become one of the most prominent components in computer vision. State-of-the-art object detectors now employ...
