The traditional pipeline for non-rigid registration is to iteratively update the correspondence and alignment such that the transformed source surface aligns well with the target *** the pipeline,the correspondence co...
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The traditional pipeline for non-rigid registration is to iteratively update the correspondence and alignment such that the transformed source surface aligns well with the target *** the pipeline,the correspondence construction and iterative manner are key to the results,while existing strategies might result in local *** this paper,we adopt the widely used deformation graph-based representation,while replacing some key modules with neural learning-based ***,we design a neural network to predict the correspondence and its reliability confidence rather than the strategies like nearest neighbor search and pair ***,we adopt the GRU-based recurrent network for iterative refinement,which is more robust than the traditional *** model is trained in a self-supervised manner and thus can be used for arbitrary datasets without *** experiments demonstrate that our proposed method outperforms the state-of-the-art methods by a large margin.
In the shape analysis community,decomposing a 3D shape intomeaningful parts has become a topic of interest.3D model segmentation is largely used in tasks such as shape deformation,shape partial matching,skeleton extra...
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In the shape analysis community,decomposing a 3D shape intomeaningful parts has become a topic of interest.3D model segmentation is largely used in tasks such as shape deformation,shape partial matching,skeleton extraction,shape correspondence,shape annotation and texture *** approaches have attempted to provide better segmentation solutions;however,the majority of the previous techniques used handcrafted features,which are usually focused on a particular attribute of 3Dobjects and so are difficult to *** this paper,we propose a three-stage approach for using Multi-view recurrent neural network to automatically segment a 3D shape into visually meaningful *** first stage involves normalizing and scaling a 3D model to fit within the unit sphere and rendering the object into different *** viewpoints,on the other hand,might not have been associated,and a 3D region could correlate into totally distinct outcomes depending on the *** address this,we ran each view through(shared weights)CNN and Bolster block in order to create a probability boundary *** Bolster block simulates the area relationships between different views,which helps to improve and refine the *** stage two,the feature maps generated in the previous step are correlated using a Recurrent Neural network to obtain compatible fine detail responses for each ***,a layer that is fully connected is used to return coherent edges,which are then back project to 3D objects to produce the final *** on the Princeton Segmentation Benchmark dataset show that our proposed method is effective for mesh segmentation tasks.
Generative artificial intelligence (GAl) has improved significantly since the emergence of ChatGPT 3.5 and is becoming an indispensable tool for many scholars, teachers, and students. This article addresses the main p...
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Cyber-physical systems (CPSs) have been used in different domains to enable automation, increase efficiency and effectiveness, and reduce the operational costs of traditional systems. CPSs come with several limitation...
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Students' feedback is an essential part of the teaching-learning process and serves as an effective instrument for continuous improvement in educational environments. The insights gathered from students' exper...
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This work introduces an intrusion detection system (IDS) tailored for industrial internet of things (IIoT) environments based on an optimized convolutional neural network (CNN) model. The model is trained on a dataset...
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Virtual reality (VR) interfaces are becoming more commonplace as the number of capable and affordable devices increases. However, VR user interfaces for common computing tasks often fail to take full advantage of the ...
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Reading and writing the Quran is a fundamental practice for Muslims worldwide. However, with the limitations of time, resources, and busy academic schedules, many Muslim students struggle to develop these essential sk...
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The idea of the traditional histogram shifting technique is to hide a message within the cover-image pixel distribution. However, the embedding capacity is limited by the peak point occurrences. To solve this problem,...
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Smart-parking solutions use sensors, cameras, and data analysis to improve parking efficiency and reduce traffic congestion. computer vision-based methods have been used extensively in recent years to tackle the probl...
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