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Text-driven 3D indoor scene generation is useful for gaming, the film industry, and AR/VR applications. However, existing methods cannot faithfully capture the room layout, nor do they allow flexible editing of individual objects in the…

Computer Vision and Pattern Recognition · Computer Science 2025-09-25 Chuan Fang , Yuan Dong , Kunming Luo , Xiaotao Hu , Rakesh Shrestha , Ping Tan

We present Text2Room, a method for generating room-scale textured 3D meshes from a given text prompt as input. To this end, we leverage pre-trained 2D text-to-image models to synthesize a sequence of images from different poses. In order to…

Computer Vision and Pattern Recognition · Computer Science 2023-09-12 Lukas Höllein , Ang Cao , Andrew Owens , Justin Johnson , Matthias Nießner

Manually creating 3D environments for AR/VR applications is a complex process requiring expert knowledge in 3D modeling software. Pioneering works facilitate this process by generating room meshes conditioned on textual style descriptions.…

Computer Vision and Pattern Recognition · Computer Science 2023-12-11 Jonas Schult , Sam Tsai , Lukas Höllein , Bichen Wu , Jialiang Wang , Chih-Yao Ma , Kunpeng Li , Xiaofang Wang , Felix Wimbauer , Zijian He , Peizhao Zhang , Bastian Leibe , Peter Vajda , Ji Hou

Advances in 3D generative AI have enabled the creation of physical objects from text prompts, but challenges remain in creating objects involving multiple component types. We present a pipeline that integrates 3D generative AI with…

In the pursuit of efficient automated content creation, procedural generation, leveraging modifiable parameters and rule-based systems, emerges as a promising approach. Nonetheless, it could be a demanding endeavor, given its intricate…

Computer Vision and Pattern Recognition · Computer Science 2024-05-30 Chunyi Sun , Junlin Han , Weijian Deng , Xinlong Wang , Zishan Qin , Stephen Gould

Virtual Reality (VR) has emerged as a powerful tool for workforce training, offering immersive, interactive, and risk-free environments that enhance skill acquisition, decision-making, and confidence. Despite its advantages, developing VR…

Computer Vision and Pattern Recognition · Computer Science 2025-08-07 Subin Raj Peter

We present a system for generating indoor scenes in response to text prompts. The prompts are not limited to a fixed vocabulary of scene descriptions, and the objects in generated scenes are not restricted to a fixed set of object…

Computer Vision and Pattern Recognition · Computer Science 2024-03-18 Rio Aguina-Kang , Maxim Gumin , Do Heon Han , Stewart Morris , Seung Jean Yoo , Aditya Ganeshan , R. Kenny Jones , Qiuhong Anna Wei , Kailiang Fu , Daniel Ritchie

Procedural materials, represented as functional node graphs, are ubiquitous in computer graphics for photorealistic material appearance design. They allow users to perform intuitive and precise editing to achieve desired visual appearances.…

Computer Vision and Pattern Recognition · Computer Science 2025-02-19 Beichen Li , Rundi Wu , Armando Solar-Lezama , Changxi Zheng , Liang Shi , Bernd Bickel , Wojciech Matusik

The advancement of diffusion models has pushed the boundary of text-to-3D object generation. While it is straightforward to composite objects into a scene with reasonable geometry, it is nontrivial to texture such a scene perfectly due to…

Computer Vision and Pattern Recognition · Computer Science 2024-06-05 Qi Wang , Ruijie Lu , Xudong Xu , Jingbo Wang , Michael Yu Wang , Bo Dai , Gang Zeng , Dan Xu

This work explores expanding the capabilities of large language models (LLMs) pretrained on text to generate 3D meshes within a unified model. This offers key advantages of (1) leveraging spatial knowledge already embedded in LLMs, derived…

Machine Learning · Computer Science 2024-11-15 Zhengyi Wang , Jonathan Lorraine , Yikai Wang , Hang Su , Jun Zhu , Sanja Fidler , Xiaohui Zeng

We present MeshLLM, a novel framework that leverages large language models (LLMs) to understand and generate text-serialized 3D meshes. Our approach addresses key limitations in existing methods, including the limited dataset scale when…

Spatial reasoning in 3D scenes requires precise geometric calculations that challenge vision-language models. Visual programming addresses this by decomposing problems into steps calling specialized tools, yet existing methods rely on…

Computer Vision and Pattern Recognition · Computer Science 2025-12-25 Shengguang Wu , Xiaohan Wang , Yuhui Zhang , Hao Zhu , Serena Yeung-Levy

We present Large Language Model for Mixed Reality (LLMR), a framework for the real-time creation and modification of interactive Mixed Reality experiences using LLMs. LLMR leverages novel strategies to tackle difficult cases where ideal…

Human-Computer Interaction · Computer Science 2024-03-25 Fernanda De La Torre , Cathy Mengying Fang , Han Huang , Andrzej Banburski-Fahey , Judith Amores Fernandez , Jaron Lanier

Given the steep learning curve of professional 3D software and the time-consuming process of managing large 3D assets, language-guided 3D scene editing has significant potential in fields such as virtual reality, augmented reality, and…

The techniques for 3D indoor scene capturing are widely used, but the meshes produced leave much to be desired. In this paper, we propose "RoomDreamer", which leverages powerful natural language to synthesize a new room with a different…

Computer Vision and Pattern Recognition · Computer Science 2023-05-22 Liangchen Song , Liangliang Cao , Hongyu Xu , Kai Kang , Feng Tang , Junsong Yuan , Yang Zhao

Despite large-scale pretraining endowing models with language and vision reasoning capabilities, improving their spatial reasoning capability remains challenging due to the lack of data grounded in the 3D world. While it is possible for…

Mixed reality (MR) environments offer embodied spatial interaction, providing intuitive 3D manipulation capabilities that enhance the conceptual design process. Parametric modeling, a powerful and advanced architectural design method,…

Human-Computer Interaction · Computer Science 2025-06-09 Ruochen Ji , Lyu Tiangang

Attaining a high degree of user controllability in visual generation often requires intricate, fine-grained inputs like layouts. However, such inputs impose a substantial burden on users when compared to simple text inputs. To address the…

Computer Vision and Pattern Recognition · Computer Science 2023-10-31 Weixi Feng , Wanrong Zhu , Tsu-jui Fu , Varun Jampani , Arjun Akula , Xuehai He , Sugato Basu , Xin Eric Wang , William Yang Wang

We introduce ChatGarment, a novel approach that leverages large vision-language models (VLMs) to automate the estimation, generation, and editing of 3D garments from images or text descriptions. Unlike previous methods that struggle in…

Computer Vision and Pattern Recognition · Computer Science 2025-04-04 Siyuan Bian , Chenghao Xu , Yuliang Xiu , Artur Grigorev , Zhen Liu , Cewu Lu , Michael J. Black , Yao Feng

We propose Prim2Room, a novel framework for controllable room mesh generation leveraging 2D layout conditions and 3D primitive retrieval to facilitate precise 3D layout specification. Diverging from existing methods that lack control and…

Computer Vision and Pattern Recognition · Computer Science 2024-09-10 Chengzeng Feng , Jiacheng Wei , Cheng Chen , Yang Li , Pan Ji , Fayao Liu , Hongdong Li , Guosheng Lin
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