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Hierarchical multi-granularity classification based on bidirectional knowledge transfer
Hierarchical multi-granularity classification is the task of classifying objects according to multiple levels or granularities. The class hierarchy...
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M2AST:MLP-mixer-based adaptive spatial-temporal graph learning for human motion prediction
Human motion prediction is a challenging task in human-centric computer vision, involving forecasting future poses based on historical sequences....
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Global adaptive histogram feature network for automatic segmentation of infection regions in CT images
Accurate and timely diagnosis of COVID-like virus is of paramount importance for lifesaving. In this work, deep learning techniques are applied to...
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Smart contract vulnerabilities detection with bidirectional encoder representations from transformers and control flow graph
Up to now, the smart contract vulnerabilities detection methods based on sequence modal data and sequence models have been the most commonly used....
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A three-stage quality evaluation method for experience products: taking animation as an example
The diversity and dynamics of quality index information bring challenges to quality assessment of experience products. This paper proposes a...
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Accurate entropy modeling in learned image compression with joint enchanced SwinT and CNN
Recently, learned image compression (LIC) has shown significant research potential. Most existing LIC methods are CNN-based or transformer-based or...
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A multi-scale no-reference video quality assessment method based on transformer
Video quality assessment is essential for optimizing user experience, enhancing network efficiency, supporting video production and editing,...
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ViCLEVR: a visual reasoning dataset and hybrid multimodal fusion model for visual question answering in Vietnamese
In recent years, visual question answering (VQA) has gained significant attention for its diverse applications, including intelligent car assistance,...
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Deep learning based features extraction for facial gender classification using ensemble of machine learning technique
Accurate and efficient gender recognition is an essential for many applications such as surveillance, security, and biometrics. Recently, deep...
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Blind quality evaluator for multi-exposure fusion image via joint sparse features and complex-wavelet statistical characteristics
Multi-Exposure Fusion (MEF) technique aims to fuse multiple images taken from the same scene at different exposure levels into an image with more...
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Context-aware adaptive network for UDA semantic segmentation
Unsupervised Domain Adaptation (UDA) plays a pivotal role in enhancing the segmentation performance of models in the target domain by mitigating the...
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Deep contrastive multi-view clustering with doubly enhanced commonality
Recently, deep multi-view clustering leveraging autoencoders has garnered significant attention due to its ability to simultaneously enhance feature...
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Quality evaluation methods of handwritten Chinese characters: a comprehensive survey
Quality evaluation of handwritten Chinese characters aims to automatically quantify and assess handwritten Chinese characters through computer vision...
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FEF-Net: feature enhanced fusion network with crossmodal attention for multimodal humor prediction
Humor segment prediction in video involves the comprehension and analysis of humor. Traditional humor prediction has been text-based; however, with...
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A channel-gained single-model network with variable rate for multispectral image compression in UAV air-to-ground remote sensing
Unmanned aerial vehicle (UAV) air-to-ground remote sensing technology, has the advantages of long flight duration, real-time image transmission, wide...
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PointDMIG: a dynamic motion-informed graph neural network for 3D action recognition
Point cloud contains rich spatial information, providing effective supplementary clues for action recognition. Existing action recognition algorithms...
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Multi-branch feature fusion and refinement network for salient object detection
With the development of convolutional neural networks (CNNs), salient object detection methods have made great progress in performance. Most methods...
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DMFNet: deep matrix factorization network for image compressed sensing
Due to its outstanding performance in image processing, deep learning (DL) is successfully utilized in compressed sensing (CS) reconstruction....
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Progressive secret image sharing based on Boolean operations and polynomial interpolations
With the expansion of network bandwidth and the rise of social networks, image sharing on open networks has become a trend. The ensuing privacy...
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Attention-guided LiDAR segmentation and odometry using image-to-point cloud saliency transfer
LiDAR odometry estimation and 3D semantic segmentation are crucial for autonomous driving, which has achieved remarkable advances recently. However,...
