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A deep convolution neural network fusing of color feature and spatio-temporal feature for smoke detection
The spatial characteristics, movement characteristics and color characteristics of smoke are important features that distinguish them to other...
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A 4D strong spatio-temporal feature learning network for behavior recognition of point cloud sequences
Although the depth map sequence widely used in behavior recognition can provide depth information. However, depth pixels are not strongly correlated...
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Convolutional Spiking Neural Networks for Spatio-Temporal Feature Extraction
Spiking neural networks (SNNs) can be used in low-power and embedded systems e.g. neuromorphic chips due to their event-based nature. They preserve...
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Video anomaly detection based on attention and efficient spatio-temporal feature extraction
An anomaly is a pattern, behavior, or event that does not frequently happen in an environment. Video anomaly detection has always been a challenging...
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Actor-Centric Spatio-Temporal Feature Extraction for Action Recognition
Action understanding involves the recognition and detection of specific actions within videos. This crucial task in computer vision gained...
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Deep video quality assessment using constrained multi-task regression and Spatio-temporal feature fusion
Many popular video quality assessment (VQA) methods usually build models by simulating the process of human visual perception and adopt a simple...
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Feature Engineering Techniques and Spatio-Temporal Data Processing
More and more applications nowadays use spatio-temporal data for different purposes. In order to be processed and used efficiently, this unique type...
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SMA-GCN: a fall detection method based on spatio-temporal relationship
With the aging population in our society, falls have become a major cause of injury to the elderly in their daily lives. Based on this, fall...
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Decoupled spatio-temporal grou** transformer for skeleton-based action recognition
Capturing correlations between joints is crucial in skeleton-based action recognition tasks. Transformer has demonstrated its capability in capturing...
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Robust Gait Recognition Based on Spatio-Temporal Fusion Network
The human gait sequence contains both spatial and temporal information, and the spatial and temporal information are restricted to different degrees...
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DSTC-Net: differential spatio-temporal correlation network for similar action recognition
Skeleton-based action recognition methods have made impressive progress. But to enhance the discrimination of similar actions, it needs to focus on...
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Semantic-guided spatio-temporal attention for few-shot action recognition
Few-shot action recognition is a challenging problem aimed at learning a model capable of adapting to recognize new categories using only a few...
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Cascading spatio-temporal attention network for real-time action detection
Accurately detecting human actions in video has many applications, such as video surveillance and somatosensory games. In this paper, we propose a...
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STAM: a spatio-temporal adaptive module for improving static convolutions in action recognition
Temporal adaptive convolution has demonstrated superior performance over static convolution techniques in video understanding. However, it needs to...
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Digital audio tampering detection based on spatio-temporal representation learning of electrical network frequency
The majority of Digital Audio Tampering Detection (DATD) methods, which are based on Electrical Network Frequency (ENF), predominantly concentrate on...
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No-reference Video Quality Assessment Based on Spatio-temporal Perception Feature Fusion
Quality assessment of real, user-generated content videos lacking reference videos is a challenging problem. For such scenarios, we propose an...
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Attribute prediction of spatio-temporal graph nodes based on weighted graph diffusion convolution network
Spatio-temporal graph data can be analyzed by effectively mining for realizing spatio-temporal graph data prediction. It is of great significance to...
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You watch once more: a more effective CNN architecture for video spatio-temporal action localization
The task of spatio-temporal action localization (STAL) needs to detect the action and position of individuals in the scene. Many works cannot model...
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Brain visual image signal classification via hybrid dilation residual shrinkage network with spatio-temporal feature fusion
Brain–computer interface (BCI) technology based on electroencephalogram (EEG) has attracted widespread attention, among which interpretation, pattern...
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STSNet: a novel spatio-temporal-spectral network for subject-independent EEG-based emotion recognition
How to use the characteristics of EEG signals to obtain more complementary and discriminative data representation is an issue in EEG-based emotion...
