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Related papers: InstructScene: Instruction-Driven 3D Indoor Scene …

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Comprehending natural language instructions is a charming property for both 2D and 3D layout synthesis systems. Existing methods implicitly model object joint distributions and express object relations, hindering generation's…

Computer Vision and Pattern Recognition · Computer Science 2025-08-05 Chenguo Lin , Yuchen Lin , Panwang Pan , Xuanyang Zhang , Yadong Mu

3D scene generation conditioned on text prompts has significantly progressed due to the development of 2D diffusion generation models. However, the textual description of 3D scenes is inherently inaccurate and lacks fine-grained control…

Computer Vision and Pattern Recognition · Computer Science 2025-01-07 Minglin Chen , Longguang Wang , Sheng Ao , Ye Zhang , Kai Xu , Yulan Guo

Controllable scene synthesis aims to create interactive environments for various industrial use cases. Scene graphs provide a highly suitable interface to facilitate these applications by abstracting the scene context in a compact manner.…

Computer Vision and Pattern Recognition · Computer Science 2024-01-02 Guangyao Zhai , Evin Pınar Örnek , Shun-Cheng Wu , Yan Di , Federico Tombari , Nassir Navab , Benjamin Busam

Designing 3D scenes is traditionally a challenging task that demands both artistic expertise and proficiency with complex software. Recent advances in text-to-3D generation have greatly simplified this process by letting users create scenes…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Zeqi Gu , Yin Cui , Zhaoshuo Li , Fangyin Wei , Yunhao Ge , Jinwei Gu , Ming-Yu Liu , Abe Davis , Yifan Ding

We present GuidedSceneGen, a text-to-3D generation framework that produces metrically accurate, globally consistent, and semantically interpretable indoor scenes. Unlike prior text-driven methods that often suffer from geometric drift or…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Stefan Ainetter , Thomas Deixelberger , Edoardo A. Dominici , Philipp Drescher , Konstantinos Vardis , Markus Steinberger

Controllability plays a crucial role in the practical applications of 3D indoor scene synthesis. Existing works either allow rough language-based control, that is convenient but lacks fine-grained scene customization, or employ graph based…

Computer Vision and Pattern Recognition · Computer Science 2025-06-04 Tongyuan Bai , Wangyuanfan Bai , Dong Chen , Tieru Wu , Manyi Li , Rui Ma

Cinematic video production requires control over scene-subject composition and camera movement, but live-action shooting remains costly due to the need for constructing physical sets. To address this, we introduce the task of cinematic…

Computer Vision and Pattern Recognition · Computer Science 2026-02-09 Kaiyi Huang , Yukun Huang , Yu Li , Jianhong Bai , Xintao Wang , Zinan Lin , Xuefei Ning , Jiwen Yu , Pengfei Wan , Yu Wang , Xihui Liu

Methods that synthesize indoor 3D scenes from text prompts have wide-ranging applications in film production, interior design, video games, virtual reality, and synthetic data generation for training embodied agents. Existing approaches…

Computer Vision and Pattern Recognition · Computer Science 2025-11-20 Antonio Ruiz , Tao Wu , Andrew Melnik , Qing Cheng , Xuqin Wang , Lu Liu , Yongliang Wang , Yanfeng Zhang , Helge Ritter

Compositional 3D scene synthesis has diverse applications across a spectrum of industries such as robotics, films, and video games, as it closely mirrors the complexity of real-world multi-object environments. Conventional works typically…

Computer Vision and Pattern Recognition · Computer Science 2024-08-27 Yao Wei , Martin Renqiang Min , George Vosselman , Li Erran Li , Michael Ying Yang

This paper presents a novel generative approach that outputs 3D indoor environments solely from a textual description of the scene. Current methods often treat scene synthesis as a mere layout prediction task, leading to rooms with…

Machine Learning · Computer Science 2025-02-12 Yao Wei , Matteo Toso , Pietro Morerio , Michael Ying Yang , Alessio Del Bue

The creation of complex 3D scenes tailored to user specifications has been a tedious and challenging task with traditional 3D modeling tools. Although some pioneering methods have achieved automatic text-to-3D generation, they are generally…

Computer Vision and Pattern Recognition · Computer Science 2025-05-09 Xiuyu Yang , Yunze Man , Jun-Kun Chen , Yu-Xiong Wang

We present a method for creating 3D indoor scenes with a generative model learned from a collection of semantic-segmented depth images captured from different unknown scenes. Given a room with a specified size, our method automatically…

Computer Vision and Pattern Recognition · Computer Science 2021-08-23 Ming-Jia Yang , Yu-Xiao Guo , Bin Zhou , Xin Tong

Despite the recent advancement of Generative Adversarial Networks (GANs) in learning 3D-aware image synthesis from 2D data, existing methods fail to model indoor scenes due to the large diversity of room layouts and the objects inside. We…

Computer Vision and Pattern Recognition · Computer Science 2022-02-21 Zifan Shi , Yujun Shen , Jiapeng Zhu , Dit-Yan Yeung , Qifeng Chen

3D indoor scene generation conditioned on short textual descriptions provides a promising avenue for interactive 3D environment construction without the need for labor-intensive layout specification. Despite recent progress in…

Computer Vision and Pattern Recognition · Computer Science 2026-04-09 Jie Feng , Jiawei Shen , Junjia Huang , Junpeng Zhang , Mingtao Feng , Weisheng Dong , Guanbin Li

Scene generation has extensive industrial applications, demanding both high realism and precise control over geometry and appearance. Language-driven retrieval methods compose plausible scenes from a large object database, but overlook…

Computer Vision and Pattern Recognition · Computer Science 2026-03-23 Zhifei Yang , Guangyao Zhai , Keyang Lu , YuYang Yin , Chao Zhang , Zhen Xiao , Jieyi Long , Nassir Navab , Yikai Wang

Text-driven 3D indoor scene generation holds broad applications, ranging from gaming and smart homes to AR/VR applications. Fast and high-fidelity scene generation is paramount for ensuring user-friendly experiences. However, existing…

Computer Vision and Pattern Recognition · Computer Science 2024-05-10 Yikun Ma , Dandan Zhan , Zhi Jin

Existing 3D-aware image synthesis approaches mainly focus on generating a single canonical object and show limited capacity in composing a complex scene containing a variety of objects. This work presents DisCoScene: a 3Daware generative…

Computer Vision and Pattern Recognition · Computer Science 2022-12-23 Yinghao Xu , Menglei Chai , Zifan Shi , Sida Peng , Ivan Skorokhodov , Aliaksandr Siarohin , Ceyuan Yang , Yujun Shen , Hsin-Ying Lee , Bolei Zhou , Sergey Tulyakov

We address the new problem of language-guided semantic style transfer of 3D indoor scenes. The input is a 3D indoor scene mesh and several phrases that describe the target scene. Firstly, 3D vertex coordinates are mapped to RGB residues by…

Computer Vision and Pattern Recognition · Computer Science 2022-08-17 Bu Jin , Beiwen Tian , Hao Zhao , Guyue Zhou

Controllable scene synthesis consists of generating 3D information that satisfy underlying specifications. Thereby, these specifications should be abstract, i.e. allowing easy user interaction, whilst providing enough interface for detailed…

Computer Vision and Pattern Recognition · Computer Science 2021-08-20 Helisa Dhamo , Fabian Manhardt , Nassir Navab , Federico Tombari

Recent breakthroughs in text-guided image generation have led to remarkable progress in the field of 3D synthesis from text. By optimizing neural radiance fields (NeRF) directly from text, recent methods are able to produce remarkable…

Computer Vision and Pattern Recognition · Computer Science 2023-03-24 Dana Cohen-Bar , Elad Richardson , Gal Metzer , Raja Giryes , Daniel Cohen-Or
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