Search
Search Results
-
Multi-head multi-order graph attention networks
The Graph Attention Network (GAT) is a type of graph neural network (GNN) that uses attention mechanisms to weigh the importance of nodes’ neighbors,...
-
Strategies for inserting attention in computer vision
Attention is increasingly used in computer vision, where both channel attention and spatial attention have proven their effectiveness in...
-
Combining channel-wise joint attention and temporal attention in graph convolutional networks for skeleton-based action recognition
Graph convolutional networks (GCNs) have been shown to be effective in performing skeleton-based action recognition, as graph topology has advantages...
-
Pyramid Attention Network for Image Restoration
Self-similarity refers to the image prior widely used in image restoration algorithms that small but similar patterns tend to occur at different...
-
Adaptive attention mechanism for single channel speech enhancement
The recent development of speech enhancement methods has incorporated attention mechanisms for learning long-term speech signal dependencies. The...
-
SCATT: Transformer tracking with symmetric cross-attention
In the popular Siamese network tracker, cross-correlation is based on the similarity to find the exact location of the template in the search region....
-
Maritime object detection using attention mechanism
The implementation of object detection in the maritime domain plays a crucial role in safeguarding maritime security, ensuring navigation safety, and...
-
Structural Dependence Learning Based on Self-attention for Face Alignment
Self-attention aggregates similar feature information to enhance the features. However, the attention covers nonface areas in face alignment, which...
-
MAN and CAT: mix attention to nn and concatenate attention to YOLO
CNNs have achieved remarkable image classification and object detection results over the past few years. Due to the locality of the convolution...
-
MANet: Mixed Attention Network for Visual Explanation
Various visual explanation methods, such as CAM and Grad-CAM, have been proposed to visualize and interpret predictions made by CNNs. Recent efforts...
-
Attention-based graph neural networks: a survey
Graph neural networks (GNNs) aim to learn well-trained representations in a lower-dimension space for downstream tasks while preserving the...
-
Generate Transferable Adversarial Physical Camouflages via Triplet Attention Suppression
Deep learning models are vulnerable to adversarial examples. As one of the most threatening types for practical deep learning systems, physical...
-
Inferring Attention Shifts for Salient Instance Ranking
The human visual system has limited capacity in simultaneously processing multiple visual inputs. Consequently, humans rely on shifting their...
-
Attention-based efficient robot grasp detection network
To balance the inference speed and detection accuracy of a grasp detection algorithm, which are both important for robot gras** tasks, we propose...
-
Multimodal attention-driven visual question answering for Malayalam
Visual question answering is a challenging task that necessitates for sophisticated reasoning over the visual elements to provide an accurate answer...
-
Position attention optimized deep semantic segmentation
Semantic segmentation can be applied in various fields of computer vision such as scene understanding. In order to assist intelligent machines to...
-
IMCN: Improved modular co-attention networks for visual question answering
Many existing Visual Question Answering (VQA) methods use traditional attention mechanisms to focus on each region of the input image and each word...
-
PPNet : pooling position attention network for semantic segmentation
Semantic segmentation with attention module has made great progress in many computer vision tasks. However, attention modules ignore some boundary...
-
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...
-
Supervised abnormal event detection based on ChatGPT attention mechanism
Aiming at the problem of abnormal target occlusion and unclearness caused by insufficient light and different shooting angles during abnormal event...
