SkexGen: Autoregressive Generation of CAD Construction Sequences with Disentangled Codebooks
Xiang Xu, Karl D. D. Willis, Joseph G. Lambourne, Chin-Yi Cheng, Pradeep Kumar Jayaraman, Yasutaka Furukawa
摘要
We present SkexGen, a novel autoregressive generative model for computer-aided design (CAD) construction sequences containing sketch-andextrude modeling operations. Our model utilizes distinct Transformer architectures to encode topological, geometric, and extrusion variations of construction sequences into disentangled codebooks. Autoregressive Transformer decoders generate CAD construction sequences sharing certain properties specified by the codebook vectors. Extensive experiments demonstrate that our disentangled codebook representation generates diverse and high-quality CAD models, enhances user control, and enables efficient exploration of the design space. The code is available at https: //samxuxiang.github.io/skexgen .
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
引用它的顶会 Paper42
- Text2CAD: Generating Sequential CAD Designs from Beginner-to-Expert Level Text PromptsMohammad Sadil Khan, Sankalp Sinha, Talha Uddin Sheikh, Didier Stricker 等NeurIPS 2024 · 被引用 148 次
- BrepGen: A B-rep Generative Diffusion Model with Structured Latent GeometryXiang Xu, Joseph G. Lambourne, Pradeep Kumar Jayaraman, Zhengqing Wang 等SIGGRAPH 2024 · 被引用 62 次
- D2CSG: Unsupervised Learning of Compact CSG Trees with Dual Complements and DropoutsFenggen Yu, Qimin Chen, Maham Tanveer, Ali Mahdavi-Amiri 等NeurIPS 2023 · 被引用 61 次
- CAD-GPT: Synthesising CAD Construction Sequence with Spatial Reasoning-Enhanced Multimodal LLMsSiyu Wang, Cailian Chen, Xinyi Le, Qimin Xu 等AAAI 2025 · 被引用 49 次
- Seek-CAD: A Self-refined Generative Modeling for 3D Parametric CAD Using Local Inference via DeepSeekXueyang Li, Jiahao Li, Yu Song, Yunzhong Lou 等ICLR 2026 · 被引用 30 次
它引用的顶会 Paper11
- An Image is Worth 16x16 Words: Transformers for Image Recognition at ScaleAlexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn 等ICLR 2021 · 被引用 21,477 次
- The Curious Case of Neural Text DegenerationAri Holtzman, Jan Buys, Li Du, Maxwell Forbes 等ICLR 2020 · 被引用 4,112 次
- DeepCAD: A Deep Generative Network for Computer-Aided Design ModelsRundi Wu, Chang Xiao, Changxi ZhengICCV 2021 · 被引用 290 次
- Fusion 360 gallery: a dataset and environment for programmatic CAD construction from human design sequencesKarl D. D. Willis, Yewen Pu, Jieliang Luo, Hang Chu 等SIGGRAPH 2021 · 被引用 197 次
- UCSG-NET- Unsupervised Discovering of Constructive Solid Geometry TreeKacper Kania, Maciej Zieba, Tomasz KajdanowiczNeurIPS 2020 · 被引用 133 次
相关 Paper
- Hierarchical Neural Coding for Controllable CAD Model GenerationXiang Xu, Pradeep Kumar Jayaraman, Joseph George Lambourne, Karl D. D. Willis 等ICML 2023 · 被引用 88 次
- SketchGen: Generating Constrained CAD SketchesWamiq Reyaz Para, Shariq Farooq Bhat, Paul Guerrero, Tom Kelly 等NeurIPS 2021 · 被引用 114 次
- Revisiting CAD Model Generation by Learning Raster SketchPu Li, Wenhao Zhang, Jianwei Guo, Jinglu Chen 等AAAI 2025 · 被引用 7 次
- CAD Translator: An Effective Drive for Text to 3D Parametric Computer-Aided Design Generative ModelingXueyang Li, Yu Song, Yunzhong Lou, Xiangdong ZhouACM MM 2024 · 被引用 16 次
- MamTiff-CAD: Multi-Scale Latent Diffusion with Mamba+ for Complex Parametric SequenceLiyuan Deng, Yunpeng Bai, Yongkang Dai, Xiaoshui Huang 等ICCV 2025 · 被引用 3 次
