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Related papers: Layout-your-3D: Controllable and Precise 3D Genera…

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Controllable layout generation aims to create plausible visual arrangements of element bounding boxes within a graphic design according to certain optional constraints, such as the type or position of a specific component. While recent…

Computer Vision and Pattern Recognition · Computer Science 2025-06-04 Yuxuan Wu , Le Wang , Sanping Zhou , Mengnan Liu , Gang Hua , Haoxiang Li

Recently, 3D generative models have made impressive progress, enabling the generation of almost arbitrary 3D assets from text or image inputs. However, these approaches generate objects in isolation without any consideration for the scene…

Computer Vision and Pattern Recognition · Computer Science 2025-05-02 Jinghao Zhou , Tomas Jakab , Philip Torr , Christian Rupprecht

Efficient authoring of vast virtual environments hinges on algorithms that are able to automatically generate content while also being controllable. We propose a method to automatically generate furniture layouts for indoor environments.…

Computer Vision and Pattern Recognition · Computer Science 2019-01-28 Paul Henderson , Kartic Subr , Vittorio Ferrari

With the onset of diffusion-based generative models and their ability to generate text-conditioned images, content generation has received a massive invigoration. Recently, these models have been shown to provide useful guidance for the…

Computer Vision and Pattern Recognition · Computer Science 2023-11-30 Alexander Vilesov , Pradyumna Chari , Achuta Kadambi

Text-to-3D modelling has seen exciting progress by combining generative text-to-image models with image-to-3D methods like Neural Radiance Fields. DreamFusion recently achieved high-quality results but requires a lengthy, per-prompt…

We propose a new generative model for layout generation. We generate layouts in three steps. First, we generate the layout elements as nodes in a layout graph. Second, we compute constraints between layout elements as edges in the layout…

Computer Vision and Pattern Recognition · Computer Science 2020-11-30 Wamiq Para , Paul Guerrero , Tom Kelly , Leonidas Guibas , Peter Wonka

We address the problem of scene layout generation for diverse domains such as images, mobile applications, documents, and 3D objects. Most complex scenes, natural or human-designed, can be expressed as a meaningful arrangement of simpler…

Computer Vision and Pattern Recognition · Computer Science 2021-10-01 Kamal Gupta , Justin Lazarow , Alessandro Achille , Larry Davis , Vijay Mahadevan , Abhinav Shrivastava

Diffusion-based generative models have significantly advanced text-to-image generation but encounter challenges when processing lengthy and intricate text prompts describing complex scenes with multiple objects. While excelling in…

Computer Vision and Pattern Recognition · Computer Science 2024-02-27 Hanan Gani , Shariq Farooq Bhat , Muzammal Naseer , Salman Khan , Peter Wonka

Despite the remarkable progress of 3D generation, achieving controllability, i.e., ensuring consistency between generated 3D content and input conditions like edge and depth, remains a significant challenge. Existing methods often struggle…

Computer Vision and Pattern Recognition · Computer Science 2025-08-14 Hongbin Xu , Chaohui Yu , Feng Xiao , Jiazheng Xing , Hai Ci , Weitao Chen , Fan Wang , Ming Li

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

Recently, multi-view diffusion-based 3D generation methods have gained significant attention. However, these methods often suffer from shape and texture misalignment across generated multi-view images, leading to low-quality 3D generation…

Computer Vision and Pattern Recognition · Computer Science 2025-11-18 Zhuojiang Cai , Yiheng Zhang , Meitong Guo , Mingdao Wang , Yuwang Wang

Recent breakthroughs in text-guided image generation have significantly advanced the field of 3D generation. While generating a single high-quality 3D object is now feasible, generating multiple objects with reasonable interactions within a…

Computer Vision and Pattern Recognition · Computer Science 2024-10-29 Chongjian Ge , Chenfeng Xu , Yuanfeng Ji , Chensheng Peng , Masayoshi Tomizuka , Ping Luo , Mingyu Ding , Varun Jampani , Wei Zhan

2D concept art generation for 3D scenes is a crucial yet challenging task in computer graphics, as creating natural intuitive environments still demands extensive manual effort in concept design. While generative AI has simplified 2D…

Computer Vision and Pattern Recognition · Computer Science 2026-02-09 Zhenhong Sun , Yifu Wang , Yonhon Ng , Yongzhi Xu , Daoyi Dong , Hongdong Li , Pan Ji

Recently, the impressive generative capabilities of diffusion models have been demonstrated, producing images with remarkable fidelity. Particularly, existing methods for the 3D object generation tasks, which is one of the fastest-growing…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Jaeseok Lee , Jaekoo Lee

Text-to-3D generation from a single-view image is a popular but challenging task in 3D vision. Although numerous methods have been proposed, existing works still suffer from the inconsistency issues, including 1) semantic inconsistency, 2)…

Computer Vision and Pattern Recognition · Computer Science 2023-09-08 Yichen Ouyang , Wenhao Chai , Jiayi Ye , Dapeng Tao , Yibing Zhan , Gaoang Wang

Text-to-3D asset generation has achieved significant optimization under the supervision of 2D diffusion priors. However, when dealing with compositional scenes, existing methods encounter several challenges: 1). failure to ensure that…

Computer Vision and Pattern Recognition · Computer Science 2025-02-04 Qixuan Li , Chao Wang , Zongjin He , Yan Peng

Generative models for 3D object synthesis have seen significant advancements with the incorporation of prior knowledge distilled from 2D diffusion models. Nevertheless, challenges persist in the form of multi-view geometric inconsistencies…

Computer Vision and Pattern Recognition · Computer Science 2023-11-20 Lincong Feng , Muyu Wang , Maoyu Wang , Kuo Xu , Xiaoli Liu

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

The creation of 3D assets with explicit, editable part structures is crucial for advancing interactive applications, yet most generative methods produce only monolithic shapes, limiting their utility. We introduce OmniPart, a novel…

Computer Vision and Pattern Recognition · Computer Science 2025-07-09 Yunhan Yang , Yufan Zhou , Yuan-Chen Guo , Zi-Xin Zou , Yukun Huang , Ying-Tian Liu , Hao Xu , Ding Liang , Yan-Pei Cao , Xihui Liu

Designing complex 3D scenes has been a tedious, manual process requiring domain expertise. Emerging text-to-3D generative models show great promise for making this task more intuitive, but existing approaches are limited to object-level…

Computer Vision and Pattern Recognition · Computer Science 2023-03-24 Ryan Po , Gordon Wetzstein