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Related papers: Text2CAD: Text to 3D CAD Generation via Technical …

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Recent advances in generative AI have unveiled significant potential for the creation of 3D content. However, current methods either apply a pre-trained 2D diffusion model with the time-consuming score distillation sampling (SDS), or a…

Computer Vision and Pattern Recognition · Computer Science 2024-03-22 Yuanxun Lu , Jingyang Zhang , Shiwei Li , Tian Fang , David McKinnon , Yanghai Tsin , Long Quan , Xun Cao , Yao Yao

We introduce Text2Immersion, an elegant method for producing high-quality 3D immersive scenes from text prompts. Our proposed pipeline initiates by progressively generating a Gaussian cloud using pre-trained 2D diffusion and depth…

Computer Vision and Pattern Recognition · Computer Science 2023-12-15 Hao Ouyang , Kathryn Heal , Stephen Lombardi , Tiancheng Sun

We introduce ProcGen3D, a new approach for 3D content creation by generating procedural graph abstractions of 3D objects, which can then be decoded into rich, complex 3D assets. Inspired by the prevalent use of procedural generators in…

Computer Vision and Pattern Recognition · Computer Science 2025-11-11 Xinyi Zhang , Daoyi Gao , Naiqi Li , Angela Dai

CAD programs, structured as parametric sequences of commands that compile into precise 3D geometries, are fundamental to accurate and efficient engineering design processes. Generating these programs from nonparametric data such as point…

Graphics · Computer Science 2025-09-22 Nomi Yu , Md Ferdous Alam , A. John Hart , Faez Ahmed

Recently, diffusion models have made significant strides in synthesizing realistic 2D human images based on provided text prompts. Building upon this, researchers have extended 2D text-to-image diffusion models into the 3D domain for…

Computer Vision and Pattern Recognition · Computer Science 2024-08-12 Weijie Wang , Jichao Zhang , Chang Liu , Xia Li , Xingqian Xu , Humphrey Shi , Nicu Sebe , Bruno Lepri

Text-to-3D generation has made remarkable progress recently, particularly with methods based on Score Distillation Sampling (SDS) that leverages pre-trained 2D diffusion models. While the usage of classifier-free guidance is well…

Computer Vision and Pattern Recognition · Computer Science 2023-11-01 Xin Yu , Yuan-Chen Guo , Yangguang Li , Ding Liang , Song-Hai Zhang , Xiaojuan Qi

Large Language Models (LLMs) are revolutionizing industries by enhancing efficiency, scalability, and innovation. This paper investigates the potential of LLMs in automating Computer-Aided Design (CAD) workflows, by integrating FreeCAD with…

Human-Computer Interaction · Computer Science 2025-08-05 Sumit Kumar , Sarthak Kapoor , Harsh Vardhan , Yao Zhao

Recent advances in text-to-image generation with diffusion models present transformative capabilities in image quality. However, user controllability of the generated image, and fast adaptation to new tasks still remains an open challenge,…

Computer Vision and Pattern Recognition · Computer Science 2023-02-17 Omer Bar-Tal , Lior Yariv , Yaron Lipman , Tali Dekel

This paper introduces a pioneering 3D volumetric encoder designed for text-to-3D generation. To scale up the training data for the diffusion model, a lightweight network is developed to efficiently acquire feature volumes from multi-view…

Computer Vision and Pattern Recognition · Computer Science 2024-08-14 Zhicong Tang , Shuyang Gu , Chunyu Wang , Ting Zhang , Jianmin Bao , Dong Chen , Baining Guo

We develop an approach for text-to-image generation that embraces additional retrieval images, driven by a combination of implicit visual guidance loss and generative objectives. Unlike most existing text-to-image generation methods which…

Computer Vision and Pattern Recognition · Computer Science 2022-08-19 Xin Yuan , Zhe Lin , Jason Kuen , Jianming Zhang , John Collomosse

Recent progress in text-to-3D generation has been achieved through the utilization of score distillation methods: they make use of the pre-trained text-to-image (T2I) diffusion models by distilling via the diffusion model training…

Computer Vision and Pattern Recognition · Computer Science 2024-03-25 Kyungmin Lee , Kihyuk Sohn , Jinwoo Shin

Generation of computer-aided design (CAD) models from multi-view images may be useful in many practical applications. To date, this problem is usually solved with an intermediate point-cloud reconstruction and involves manual work to create…

Computer Vision and Pattern Recognition · Computer Science 2023-09-26 Henrik Jobczyk , Hanno Homann

Denoising diffusion models trained at web-scale have revolutionized image generation. The application of these tools to engineering design is an intriguing possibility, but is currently limited by their inability to parse and enforce…

Machine Learning · Computer Science 2023-06-19 Nikos Arechiga , Frank Permenter , Binyang Song , Chenyang Yuan

3D world generation is essential for applications such as immersive content creation or autonomous driving simulation. Recent advances in 3D world generation have shown promising results; however, these methods are constrained by grid…

Computer Vision and Pattern Recognition · Computer Science 2026-05-04 Jaeyoung Chung , Suyoung Lee , Jianfeng Xiang , Jiaolong Yang , Kyoung Mu Lee

Text-to-3D with diffusion models has achieved remarkable progress in recent years. However, existing methods either rely on score distillation-based optimization which suffer from slow inference, low diversity and Janus problems, or are…

Computer Vision and Pattern Recognition · Computer Science 2023-11-27 Jiahao Li , Hao Tan , Kai Zhang , Zexiang Xu , Fujun Luan , Yinghao Xu , Yicong Hong , Kalyan Sunkavalli , Greg Shakhnarovich , Sai Bi

Recent techniques for text-to-4D generation synthesize dynamic 3D scenes using supervision from pre-trained text-to-video models. However, existing representations for motion, such as deformation models or time-dependent neural…

Computer Vision and Pattern Recognition · Computer Science 2024-10-16 Sherwin Bahmani , Xian Liu , Wang Yifan , Ivan Skorokhodov , Victor Rong , Ziwei Liu , Xihui Liu , Jeong Joon Park , Sergey Tulyakov , Gordon Wetzstein , Andrea Tagliasacchi , David B. Lindell

Recent text-to-scene generation approaches largely reduced the manual efforts required to create 3D scenes. However, their focus is either to generate a scene layout or to generate objects, and few generate both. The generated scene layout…

Computer Vision and Pattern Recognition · Computer Science 2026-04-30 Zhenggang Tang , Yuehao Wang , Yuchen Fan , Jun-Kun Chen , Yu-Ying Yeh , Kihyuk Sohn , Zhangyang Wang , Qixing Huang , Alexander Schwing , Rakesh Ranjan , Dilin Wang , Zhicheng Yan

Image and shape editing are ubiquitous among digital artworks. Graphics algorithms facilitate artists and designers to achieve desired editing intents without going through manually tedious retouching. In the recent advance of machine…

Graphics · Computer Science 2023-04-20 Cheng-Kang Ted Chao , Yotam Gingold

Generating 3D models lies at the core of computer graphics and has been the focus of decades of research. With the emergence of advanced neural representations and generative models, the field of 3D content generation is developing rapidly,…

Computer Vision and Pattern Recognition · Computer Science 2024-02-01 Xiaoyu Li , Qi Zhang , Di Kang , Weihao Cheng , Yiming Gao , Jingbo Zhang , Zhihao Liang , Jing Liao , Yan-Pei Cao , Ying Shan

Recent advances in diffusion models have revolutionized 2D and 3D content creation, yet generating photorealistic dynamic 4D scenes remains a significant challenge. Existing dynamic 4D generation methods typically rely on distilling…

Computer Vision and Pattern Recognition · Computer Science 2025-04-01 Vinayak Gupta , Yunze Man , Yu-Xiong Wang