In the new era of technology,daily human activities are becoming more challenging in terms of monitoring complex scenes and *** understand the scenes and activities from human life logs,human-object interaction(HOI)is...
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In the new era of technology,daily human activities are becoming more challenging in terms of monitoring complex scenes and *** understand the scenes and activities from human life logs,human-object interaction(HOI)is important in terms of visual relationship detection and human pose *** understanding and interaction recognition between human and object along with the pose estimation and interaction modeling have been *** existing algorithms and feature extraction procedures are complicated including accurate detection of rare human postures,occluded regions,and unsatisfactory detection of objects,especially small-sized *** existing HOI detection techniques are instancecentric(object-based)where interaction is predicted between all the *** estimation depends on appearance features and spatial ***,we propose a novel approach to demonstrate that the appearance features alone are not sufficient to predict the ***,we detect the human body parts by using the Gaussian Matric Model(GMM)followed by object detection using *** predict the interaction points which directly classify the interaction and pair them with densely predicted HOI vectors by using the interaction *** interactions are linked with the human and object to predict the *** experiments have been performed on two benchmark HOI datasets demonstrating the proposed approach.
Rapid and accurate detection of the power battery pole area before welding is the prerequisite for accurately locating the welding starting point, and its performance determines the assembly efficiency and quality of ...
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We consider the rate-limited quantum-to-classical optimal transport in terms of output-constrained rate-distortion coding for discrete quantum measurement systems with limited classical common randomness. The main cod...
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In an application involving Autonomous Underwater Vehicles (AUV) it is important to track the trajectory and spatially correlate the collected data. Relying on an Inertial Navigation System (INS) while factoring in th...
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We study the problem of inferring user intent from noninvasive electroencephalography (EEG) to restore communication for people with severe speech and physical impairments (SSPI). The focus of this work is improving t...
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This paper studies the fundamental limits of the shared-link coded caching problem with correlated files, where a server with a library of N files communicates with K users who can locally cache M files. Given an inte...
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Invariant Risk Minimization is a well-known Domain Generalization framework that has received much attention over the past few years. Invariant Risk Minimization is capable of learning domain-invariant features from m...
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With the rapid development of new power systems, combined with global warming and other background, the new power system faces an obvious increase in extreme disaster weather events such as lightning. The intensive ch...
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The two-dimensional target localization problem for a network of distributed sensor sub-arrays (with a sub-array at each receiver) is investigated in the compressive sensing framework based on group sparsity, and the ...
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