TL;DR
This paper introduces CADSketchNet, a new annotated sketch dataset for 3D CAD model retrieval using deep neural networks, and evaluates various models for sketch-based search of CAD models.
Contribution
The creation of CADSketchNet, a comprehensive dataset combining computer-generated and hand-drawn sketches for 3D CAD model retrieval, and the evaluation of deep learning retrieval models.
Findings
Deep learning models can effectively retrieve 3D CAD models from sketches.
CADSketchNet improves the development of sketch-based CAD retrieval systems.
Experimental results demonstrate promising retrieval accuracy.
Abstract
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…
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