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Staged Transformer Network with Color Harmonization for Image Outpainting
Image outpainting aims at generating new looking-realistic content beyond the original boundaries for a given image patch. Existing image outpainting...
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CTNet: hybrid architecture based on CNN and transformer for image inpainting detection
Digital image inpainting technology has increasingly gained popularity as a result of the development of image processing and machine vision....
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Attention and Multi-granied Feature Learning for Baggage Re-identification
The current baggage re-identification methods only consider the global coarse-grained features while ignoring the fine-grained features. To deal with...
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Graph convolutional dynamic recurrent network with attention for traffic forecasting
Traffic forecasting is a typical spatio-temporal graph modeling problem, which has become one of the key technical issues in modern intelligent...
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Semantic segmentation of breast cancer images using DenseNet with proposed PSPNet
For early detection of cancer tumors, the semantic segmentation based technique is proposed because the existing numerous methods fail while...
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ARFP: A novel adaptive recursive feature pyramid for object detection in aerial images
The aerial image is one of the most important application fields of object detection. However, the characteristics of scale variation in aerial...
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HPA-Net: Hierarchical and Parallel Aggregation Network for Context Learning in Stereo Matching
Accurate disparity estimation with regard to rectified stereo image pairs is essential for many computer vision tasks. Current deep learning-based...
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Context-Enhanced Representation Learning for Single Image Deraining
Perception of content and structure in images with rainstreaks or raindrops is challenging, and it often calls for robust deraining algorithms to...
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A Lightweight Dual Branch Fusion Network for Single Image Deraining
Transformers have shown promise in high-level vision tasks, but their direct application to low-level vision can lead to artifacts and high...
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SDGC-YOLOv5: A More Accurate Model for Small Object Detection
Small objects often suffer from size and resolution limitations, resulting in poor detection performance when employing traditional object detection...
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Cascaded Global Context Convolutional Neural Network for Brain Tumor Segmentation
A cascade of global context convolutional neural networks is proposed to segment multi-modality MR images with brain tumor into three subregions:...
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GlcMatch: global and local constraints for reliable feature matching
A match is considered as an incorrect match when the matched features in two views do not correspond to the same physical location. It is inevitable...
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DGFAU-Net: Global feature attention upsampling network for medical image segmentation
Medical image segmentation plays an important role in many clinical medicines, such as medical diagnosis and computer-assisted treatment. However,...
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Faster learning of temporal action proposal via sparse multilevel boundary generator
Temporal action localization in videos presents significant challenges in the field of computer vision. While the boundary-sensitive method has been...
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Research on the application of high-efficiency detectors into the detection of prohibited item in X-ray images
X-ray imaging can be used to inspect the internal structure of the objects without destruction, so visual inspection based on X-ray images is widely...
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Local and Non-local Context Graph Convolutional Networks for Skeleton-Based Action Recognition
Graph convolutional networks (GCNs) for skeleton-based action recognition have achieved considerable progress recently. However, there are still two...
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3T-IEC*: a context-aware recommender system architecture for smart social networks (EBSN and SBSN)
Recommending Smart Social Network (SSN) items which are in line with user preferences is one of the significant applications in SSNs such as...
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MVPN: Multi-granularity visual prompt-guided fusion network for multimodal named entity recognition
Multimodal named entity recognition (MNER) aims at identifying entity spans and recognizing their categories in social media posts with the aid of...
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Supervised biadjacency networks for stereo matching
Convolutional neural network (CNN) based stereo matching methods using cost volume techniques have gained prominence in stereo matching....
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MD-TransUNet: TransUNet with Multi-attention and Dilated Convolution for Brain Stroke Lesion Segmentation
The accurate segmentation of stroke lesion regions holds immense significance in sha** treatment strategies and rehabilitation protocols. Due to...