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UniTracker: transformer-based CrossUnihead for multi-object tracking
In recent years, tracking-by-detection (TBD) has emerged as the predominant approach for Multi-object Tracking (MOT). Most TBD algorithms typically...
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Virtual reality exposure effect in acrophobia: psychological and physiological evidence from a single experimental session
In recent years, virtual reality (VR) has gained attention from researchers in diverse fields, particularly in therapy of phobias. Currently, virtual...
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A resource-efficient partial 3D convolution for gesture recognition
3DCNNs have shown impressive capabilities in extracting spatiotemporal features from videos. However, in practical applications, the numerous...
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3D-Scene-Former: 3D scene generation from a single RGB image using Transformers
3D scene generation requires complex hardware setups, such as multiple cameras and depth sensors. To address this challenge, there is a need for...
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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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Cognitive differences in product shape evaluation between real settings and virtual reality: case study of two-wheel electric vehicles
Product shape evaluation is an important part of new product development. In the shape design stage, design schemes are often presented through...
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Combinatorial refinement on circulant graphs
The combinatorial refinement techniques have proven to be an efficient approach to isomorphism testing for particular classes of graphs. If the...
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Sublinear Algorithms in T-Interval Dynamic Networks
We consider standard T - interval dynamic networks , under the synchronous timing model and the broadcast CONGEST model. In a T - interval dynamic network ,...
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Learning to sculpt neural cityscapes
We introduce a system that learns to sculpt 3D models of massive urban environments. The majority of humans live their lives in urban environments,...
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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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A full-detection association tracker with confidence optimization for real-time multi-object tracking
Multi-object tracking (MOT) aims to obtain trajectories with unique identifiers for multiple objects in a video stream. In current approaches,...
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ACL-SAR: model agnostic adversarial contrastive learning for robust skeleton-based action recognition
Human skeleton data have been widely explored in action recognition and the human–computer interface recently, thanks to off-the-shelf motion sensors...
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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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Real-time and secure identity authentication transmission mechanism for artificial intelligence generated image content
The rapid development of generative artificial intelligence technology and large-scale pre-training models has led to the emergence of artificial...
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Intersecting realms: a cross-disciplinary examination of VR quality of experience research
The advent of virtual reality (VR) technology has necessitated a reevaluation of quality of experience (QoE) models. While numerous recent efforts...
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Usability of visualizing position and orientation deviations for manual precise manipulation of objects in augmented reality
Manual precise manipulation of objects is an essential skill in everyday life, and Augmented Reality (AR) is increasingly being used to support such...
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Autocleandeepfood: auto-cleaning and data balancing transfer learning for regional gastronomy food computing
Food computing has emerged as a promising research field, employing artificial intelligence, deep learning, and data science methodologies to enhance...
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A novel single kernel parallel image encryption scheme based on a chaotic map
The development of communication technologies has increased concerns about data security, increasing the prominence of cryptography. Images are one...
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Continual few-shot patch-based learning for anime-style colorization
The automatic colorization of anime line drawings is a challenging problem in production pipelines. Recent advances in deep neural networks have...
