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Related papers: SketchGen: Generating Constrained CAD Sketches

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Parametric computer-aided design (CAD) is the dominant paradigm in mechanical engineering for physical design. Distinguished by relational geometry, parametric CAD models begin as two-dimensional sketches consisting of geometric primitives…

Machine Learning · Computer Science 2020-07-17 Ari Seff , Yaniv Ovadia , Wenda Zhou , Ryan P. Adams

Engineering sketches form the 2D basis of parametric Computer-Aided Design (CAD), the foremost modeling paradigm for manufactured objects. In this paper we tackle the problem of learning based engineering sketch generation as a first step…

Machine Learning · Computer Science 2021-04-21 Karl D. D. Willis , Pradeep Kumar Jayaraman , Joseph G. Lambourne , Hang Chu , Yewen Pu

Parametric computer-aided design (CAD) tools are the predominant way that engineers specify physical structures, from bicycle pedals to airplanes to printed circuit boards. The key characteristic of parametric CAD is that design intent is…

Machine Learning · Computer Science 2022-04-29 Ari Seff , Wenda Zhou , Nick Richardson , Ryan P. Adams

We adapt alignment techniques from reasoning LLMs to the task of generating engineering sketch constraints found in computer-aided design (CAD) models. Engineering sketches consist of geometric primitives (e.g. points, lines) connected by…

The design and analysis of Computer-Aided Design (CAD) sketches play a crucial role in industrial product design, primarily involving CAD primitives and their inter-primitive constraints. To address challenges related to error accumulation…

Computer Vision and Pattern Recognition · Computer Science 2024-07-02 Xiaogang Wang , Liang Wang , Hongyu Wu , Guoqiang Xiao , Kai Xu

Computer-Aided Design (CAD) applications are used in manufacturing to model everything from coffee mugs to sports cars. These programs are complex and require years of training and experience to master. A component of all CAD models…

Computer Vision and Pattern Recognition · Computer Science 2021-05-07 Yaroslav Ganin , Sergey Bartunov , Yujia Li , Ethan Keller , Stefano Saliceti

We present a sketch-based CAD modeling system, where users create objects incrementally by sketching the desired shape edits, which our system automatically translates to CAD operations. Our approach is motivated by the close similarities…

Graphics · Computer Science 2020-09-11 Changjian Li , Hao Pan , Adrien Bousseau , Niloy J. Mitra

Computer-Aided Design (CAD) generative modeling is driving significant innovations across industrial applications. Recent works have shown remarkable progress in creating solid models from various inputs such as point clouds, meshes, and…

Computer Vision and Pattern Recognition · Computer Science 2025-09-12 Feiwei Qin , Shichao Lu , Junhao Hou , Changmiao Wang , Meie Fang , Ligang Liu

Sketching is an important activity in any design process. Designers and stakeholders share their ideas through hand-drawn sketches. These sketches are further used to create 3D models. Current methods to generate 3D models from sketches are…

Computer Vision and Pattern Recognition · Computer Science 2022-04-12 Nitish Bhardwaj , Dhornala Bharadwaj , Alpana Dubey

The integration of deep generative networks into generating Computer-Aided Design (CAD) models has garnered increasing attention over recent years. Traditional methods often rely on discrete sequences of parametric line/curve segments to…

Graphics · Computer Science 2025-03-04 Pu Li , Wenhao Zhang , Jianwei Guo , Jinglu Chen , Dong-Ming Yan

Graphic layout generation is a growing research area focusing on generating aesthetically pleasing layouts ranging from poster designs to documents. While recent research has explored ways to incorporate user constraints to guide the layout…

We present SkexGen, a novel autoregressive generative model for computer-aided design (CAD) construction sequences containing sketch-and-extrude modeling operations. Our model utilizes distinct Transformer architectures to encode…

Computer Vision and Pattern Recognition · Computer Science 2022-07-12 Xiang Xu , Karl D. D. Willis , Joseph G. Lambourne , Chin-Yi Cheng , Pradeep Kumar Jayaraman , Yasutaka Furukawa

Developing fully parametric building models for performance-based generative design tasks often requires proficiency in many advanced 3D modeling and visual programming, limiting its use for many building designers. Moreover, iterations of…

Human-Computer Interaction · Computer Science 2020-09-02 Mohammad Keshavarzi , Clayton Hutson , Chin-Yi Cheng , Mehdi Nourbakhsh , Michael Bergin , Mohammad Rahmani Asl

Drawing freehand sketches of mechanical components on multimedia devices for AI-based engineering modeling has become a new trend. However, its development is being impeded because existing works cannot produce suitable sketches for…

Computer Vision and Pattern Recognition · Computer Science 2024-08-22 Zhichao Liao , Di Huang , Heming Fang , Yue Ma , Fengyuan Piao , Xinghui Li , Long Zeng , Pingfa Feng

Parametric Computer-Aided Design (CAD) is central to contemporary mechanical design. However, it encounters challenges in achieving precise parametric sketch modeling and lacks practical evaluation metrics suitable for mechanical design. We…

Computer Vision and Pattern Recognition · Computer Science 2024-09-27 Sifan Wu , Amir Khasahmadi , Mor Katz , Pradeep Kumar Jayaraman , Yewen Pu , Karl Willis , Bang Liu

In this paper we investigate image generation guided by hand sketch. When the input sketch is badly drawn, the output of common image-to-image translation follows the input edges due to the hard condition imposed by the translation process.…

Computer Vision and Pattern Recognition · Computer Science 2018-07-27 Yongyi Lu , Shangzhe Wu , Yu-Wing Tai , Chi-Keung Tang

Significant progress has recently been made in creative applications of large pre-trained models for downstream tasks in 3D vision, such as text-to-shape generation. This motivates our investigation of how these pre-trained models can be…

Computer Vision and Pattern Recognition · Computer Science 2023-07-11 Aditya Sanghi , Pradeep Kumar Jayaraman , Arianna Rampini , Joseph Lambourne , Hooman Shayani , Evan Atherton , Saeid Asgari Taghanaki

We present SketchGPT, a flexible framework that employs a sequence-to-sequence autoregressive model for sketch generation, and completion, and an interpretation case study for sketch recognition. By mapping complex sketches into simplified…

Computer Vision and Pattern Recognition · Computer Science 2024-05-07 Adarsh Tiwari , Sanket Biswas , Josep Lladós

Existing text-based 3D generation methods generate attractive results but lack detailed geometry control. Sketches, known for their conciseness and expressiveness, have contributed to intuitive 3D modeling but are confined to producing…

Graphics · Computer Science 2024-05-15 Feng-Lin Liu , Hongbo Fu , Yu-Kun Lai , Lin Gao

3D Content Generation is at the heart of many computer graphics applications, including video gaming, film-making, virtual and augmented reality, etc. This paper proposes a novel deep-learning based approach for automatically generating…

Computer Vision and Pattern Recognition · Computer Science 2026-02-09 Yongzhi Xu , Yonhon Ng , Yifu Wang , Inkyu Sa , Yunfei Duan , Zhenhong Sun , Yang Li , Pan Ji , Hongdong Li
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