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Related papers: ControlRoom3D: Room Generation using Semantic Prox…

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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

We present SemLayoutDiff, a unified model for synthesizing diverse 3D indoor scenes across multiple room types. The model introduces a scene layout representation combining a top-down semantic map and attributes for each object. Unlike…

Graphics · Computer Science 2025-09-09 Xiaohao Sun , Divyam Goel , Angel X. Chang

Scene synthesis and editing has emerged as a promising direction in computer graphics. Current trained approaches for 3D indoor scene generation either oversimplify object semantics through one-hot class encodings (e.g., 'chair' or…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Martin JJ. Bucher , Iro Armeni

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

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

If a picture is worth thousand words, a moving 3d shape must be worth a million. We build upon the success of recent generative methods that create images fitting the semantics of a text prompt, and extend it to the controlled generation of…

Machine Learning · Computer Science 2021-09-28 Nikolay Jetchev

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

3D animation is central to modern visual media, yet traditional production pipelines remain labor-intensive, expertise-demanding, and computationally expensive. Recent AIGC-based approaches partially automate asset creation and rigging, but…

Computer Vision and Pattern Recognition · Computer Science 2025-12-22 Yupeng Zhu , Xiongzhen Zhang , Ye Chen , Bingbing Ni

Urban modeling is essential for city planning, scene synthesis, and gaming. Existing image-based methods generate diverse layouts but often lack geometric continuity and scalability, while graph-based methods capture structural relations…

Computer Vision and Pattern Recognition · Computer Science 2025-09-30 Mengyuan Niu , Xinxin Zhuo , Ruizhe Wang , Yuyue Huang , Junyan Yang , Qiao Wang

Mesh is a fundamental representation of 3D assets in various industrial applications, and is widely supported by professional softwares. However, due to its irregular structure, mesh creation and manipulation is often time-consuming and…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Zhaoyang Lyu , Ben Fei , Jinyi Wang , Xudong Xu , Ya Zhang , Weidong Yang , Bo Dai

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

Despite recent advancements in text-to-image generation, most existing methods struggle to create images with multiple objects and complex spatial relationships in the 3D world. To tackle this limitation, we introduce a generic AI system,…

Computer Vision and Pattern Recognition · Computer Science 2024-12-17 Yanbo Ding , Shaobin Zhuang , Kunchang Li , Zhengrong Yue , Yu Qiao , Yali Wang

As several industries are moving towards modeling massive 3D virtual worlds, the need for content creation tools that can scale in terms of the quantity, quality, and diversity of 3D content is becoming evident. In our work, we aim to train…

Computer Vision and Pattern Recognition · Computer Science 2022-09-23 Jun Gao , Tianchang Shen , Zian Wang , Wenzheng Chen , Kangxue Yin , Daiqing Li , Or Litany , Zan Gojcic , Sanja Fidler

Recent remarkable advances in large-scale text-to-image diffusion models have inspired a significant breakthrough in text-to-3D generation, pursuing 3D content creation solely from a given text prompt. However, existing text-to-3D…

Computer Vision and Pattern Recognition · Computer Science 2023-11-10 Yang Chen , Yingwei Pan , Yehao Li , Ting Yao , Tao Mei

Recent advancements in implicit 3D representations and generative models have markedly propelled the field of 3D object generation forward. However, it remains a significant challenge to accurately model geometries with defined sharp…

Graphics · Computer Science 2024-01-17 Zeqing Yuan , Haoxuan Lan , Qiang Zou , Junbo Zhao

We introduce ShowRoom3D, a three-stage approach for generating high-quality 3D room-scale scenes from texts. Previous methods using 2D diffusion priors to optimize neural radiance fields for generating room-scale scenes have shown…

Computer Vision and Pattern Recognition · Computer Science 2023-12-22 Weijia Mao , Yan-Pei Cao , Jia-Wei Liu , Zhongcong Xu , Mike Zheng Shou

Automatically generating high-quality real world 3D scenes is of enormous interest for applications such as virtual reality and robotics simulation. Towards this goal, we introduce NeuralField-LDM, a generative model capable of synthesizing…

Computer Vision and Pattern Recognition · Computer Science 2023-04-20 Seung Wook Kim , Bradley Brown , Kangxue Yin , Karsten Kreis , Katja Schwarz , Daiqing Li , Robin Rombach , Antonio Torralba , Sanja Fidler

Simulation has become a key tool for training and evaluating home robots at scale, yet existing environments fail to capture the diversity and physical complexity of real indoor spaces. Current scene synthesis methods produce sparsely…

Robotics · Computer Science 2026-02-12 Nicholas Pfaff , Thomas Cohn , Sergey Zakharov , Rick Cory , Russ Tedrake

3D indoor scene generation is an important problem for the design of digital and real-world environments. To automate this process, a scene generation model should be able to not only generate plausible scene layouts, but also take into…

Computer Vision and Pattern Recognition · Computer Science 2025-03-26 Kelly O. Marshall , Omid Poursaeed , Sergiu Oprea , Amit Kumar , Anushrut Jignasu , Chinmay Hegde , Yilei Li , Rakesh Ranjan

Generating immersive 3D scenes from texts is a core task in computer vision, crucial for applications in virtual reality and game development. Despite the promise of leveraging 2D diffusion priors, existing methods suffer from spatial…

Computer Vision and Pattern Recognition · Computer Science 2026-01-28 Jisheng Chu , Wenrui Li , Rui Zhao , Wangmeng Zuo , Shifeng Chen , Xiaopeng Fan