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Titlebook: Computer-Aided Design and Computer Graphics; 18th International C Shi-Min Hu,Yiyu Cai,Paul Rosin Conference proceedings 2024 The Editor(s)

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書目名稱Computer-Aided Design and Computer Graphics
副標(biāo)題18th International C
編輯Shi-Min Hu,Yiyu Cai,Paul Rosin
視頻videohttp://file.papertrans.cn/235/234428/234428.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Computer-Aided Design and Computer Graphics; 18th International C Shi-Min Hu,Yiyu Cai,Paul Rosin Conference proceedings 2024 The Editor(s)
描述This book constitutes the proceedings of the CCF 18th International Conference on?Computer-Aided Design and Computer Graphics, CAD/Graphics 2023, which took place in?Shanghai, China, during August 19–21, 2023..The 23 full papers included in this book were carefully reviewed and selected from 169 submissions. They focus on topics such as?computer graphics and CAD, 3D Printing and Computational Fabrication, 3D Vision, Bio-CAD and Nano-CAD, Computer Animation, Deep Learning?for Graphics, Geometric Modeling, Geometry Processing, Rendering, Virtual Reality, Augmented Reality, Visualization, and more.?.
出版日期Conference proceedings 2024
關(guān)鍵詞3D vision; Bio-CAD and Nano-CAD; computer animation; deep learning for graphics; geometric modeling; geom
版次1
doihttps://doi.org/10.1007/978-981-99-9666-7
isbn_softcover978-981-99-9665-0
isbn_ebook978-981-99-9666-7Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
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,FFANet: Dual Attention-Based Flow Field Aware Network for?3D Grid Classification and?Segmentation,te the great success in various scenarios, the existing approaches fail to effectively utilize the velocity information in the flow field, resulting in the actual requirements of post-processing tasks being difficult to meet by the extracted features. To fully integrate structural information in the
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,A Lightweight Model for?Feature Points Recognition of?Tool Path Based on?Deep Learning,r method encodes CL points as matrices and stores them as text files. We have developed a neural network with an Encoder-Decoder architecture, named EDFP-Net, which takes the encoding matrices as input, extracts deeper features using the Encoder, and recognizes feature points using the Decoder. Our
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Influence of the Printing Direction on the Surface Appearance in Multi-material Fused Filament Fabrsurface appearance is largely a matter of trial and error unless the employed materials are very similar and very translucent, so we can think of them as blending together. When the multiple materials are fused into one filament in a diamond hotend extruder but do not blend, the resulting surface ap
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StrongOC-SORT: Make Observation-Centric SORT More Robust,ositions and disturbed tracks. Despite great progress made by current trackers, their performance still needs improvement due to their inability to adapt their components to these challenges. In this work, we propose a new method, StrongOC-SORT, which exploits the observation-centric nature and four
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,Semi-direct Sparse Odometry with?Robust and?Accurate Pose Estimation for?Dynamic Scenes, with moving objects. This paper addresses the problem by proposing a semi-direct sparse visual odometry (SDSO) method designed for dynamic scenes. With the aid of the pixel-level semantic information, the system can not only eliminate dynamic points but also construct more accurate photometric erro
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,Parallel Dense Vision Transformer and?Augmentation Network for?Occluded Person Re-identification,s across different devices. Some existing methods mainly focus on developing effective data augmentation and representation learning techniques to improve the performance of person ReID systems. However, existing data augmentation strategies can not make full use of the information in the training d
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