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‘CADSketchNet’ - An Annotated Sketch dataset for 3D CAD Model Retrieval with Deep Neural Networks
Computers & Graphics ( IF 2.5 ) Pub Date : 2021-07-08 , DOI: 10.1016/j.cag.2021.07.001
Bharadwaj Manda , Shubham Dhayarkar , Sai Mitheran , V.K. Viekash , Ramanathan Muthuganapathy

Ongoing advancements in the fields of 3D modelling and digital archiving have led to an outburst in the amount of data stored digitally. Consequently, several retrieval systems have been developed depending on the type of data stored in these databases. However, unlike text data or images, performing a search for 3D models is non-trivial. Among 3D models, retrieving 3D Engineering/CAD models or mechanical components is even more challenging due to the presence of holes, volumetric features, presence of sharp edges etc., which make CAD a domain unto itself. The research work presented in this paper aims at developing a dataset suitable for building a retrieval system for 3D CAD models based on deep learning. 3D CAD models from the available CAD databases are collected, and a dataset of computer-generated sketch data, termed ‘CADSketchNet’, has been prepared. Additionally, hand-drawn sketches of the components are also added to CADSketchNet. Using the sketch images from this dataset, the paper also aims at evaluating the performance of various retrieval system or a search engine for 3D CAD models that accepts a sketch image as the input query. Many experimental models are constructed and tested on CADSketchNet. These experiments, along with the model architecture, choice of similarity metrics are reported along with the search results.



中文翻译:

'CADSketchNet' - 用于使用深度神经网络进行 3D CAD 模型检索的带注释的草图数据集

3D 建模和数字存档领域的不断进步导致以数字方式存储的数据量激增。因此,已经根据存储在这些数据库中的数据类型开发了几种检索系统。但是,与文本数据或图像不同,执行 3D 模型搜索并非易事。在 3D 模型中,检索 3D 工程/CAD 模型或机械组件更具挑战性,因为存在孔洞、体积特征、锐边等,这使 CAD 成为一个独立的领域。本文提出的研究工作旨在开发适用于构建基于深度学习的 3D CAD 模型检索系统的数据集。收集来自可用 CAD 数据库的 3D CAD 模型,以及计算机生成的草图数据数据集,称为“CADSketchNet”,已经准备好了。此外,CADsketchNet 还添加了组件的手绘草图。使用来自该数据集的草图图像,本文还旨在评估各种检索系统或接受草图图像作为输入查询的 3D CAD 模型的搜索引擎的性能。许多实验模型是在 CADsketchNet 上构建和测试的。这些实验、模型架构、相似性度量的选择与搜索结果一起报告。许多实验模型是在 CADsketchNet 上构建和测试的。这些实验以及模型架构、相似性度量的选择与搜索结果一起报告。许多实验模型是在 CADsketchNet 上构建和测试的。这些实验以及模型架构、相似性度量的选择与搜索结果一起报告。

更新日期:2021-07-20
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