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Related papers: Prim2Room: Layout-Controllable Room Mesh Generatio…

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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

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

Despite significant recent progress on generative models, controlled generation of images depicting multiple and complex object layouts is still a difficult problem. Among the core challenges are the diversity of appearance a given object…

Computer Vision and Pattern Recognition · Computer Science 2019-10-16 Bo Zhao , Lili Meng , Weidong Yin , Leonid Sigal

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

Recent progress in robot learning has been driven by large-scale datasets and powerful visuomotor policy architectures, yet policy robustness remains limited by the substantial cost of collecting diverse demonstrations, particularly for…

Robotics · Computer Science 2026-03-24 Yujie Zhao , Hongwei Fan , Di Chen , Shengcong Chen , Liliang Chen , Xiaoqi Li , Guanghui Ren , Hao Dong

Capturing both geometry and rigid motion for structured dynamic objects, like multi-part assemblies or jointed mechanisms, remains a key challenge. Existing dynamic methods, such as deformable meshes or 3DGS, rely on unstructured…

Computer Vision and Pattern Recognition · Computer Science 2026-04-21 Xingyuan Yu , Yijin Li , Chong Zeng , Yuhang Ming , Hujun Bao , Guofeng Zhang

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

We present Programmable-Room, a framework which interactively generates and edits a 3D room mesh, given natural language instructions. For precise control of a room's each attribute, we decompose the challenging task into simpler steps such…

Computer Vision and Pattern Recognition · Computer Science 2025-06-24 Jihyun Kim , Junho Park , Kyeongbo Kong , Suk-Ju Kang

Automatic furniture layout is long desired for convenient interior design. Leveraging the remarkable visual reasoning capabilities of multimodal large language models (MLLMs), recent methods address layout generation in a static manner,…

Computer Vision and Pattern Recognition · Computer Science 2024-08-01 Can Wang , Hongliang Zhong , Menglei Chai , Mingming He , Dongdong Chen , Jing Liao

We introduce Scan2Mesh, a novel data-driven generative approach which transforms an unstructured and potentially incomplete range scan into a structured 3D mesh representation. The main contribution of this work is a generative neural…

Computer Vision and Pattern Recognition · Computer Science 2019-04-03 Angela Dai , Matthias Nießner

In this paper, we propose RoomPlanner, the first fully automatic 3D room generation framework for painlessly creating realistic indoor scenes with only short text as input. Without any manual layout design or panoramic image guidance, our…

Computer Vision and Pattern Recognition · Computer Science 2025-11-24 Wenzhuo Sun , Mingjian Liang , Wenxuan Song , Xuelian Cheng , Zongyuan Ge

We present Blocks2World, a novel method for 3D scene rendering and editing that leverages a two-step process: convex decomposition of images and conditioned synthesis. Our technique begins by extracting 3D parallelepipeds from various…

Computer Vision and Pattern Recognition · Computer Science 2023-07-14 Vaibhav Vavilala , Seemandhar Jain , Rahul Vasanth , Anand Bhattad , David Forsyth

Recent 3D-based manipulation methods either directly predict the grasp pose using 3D neural networks, or solve the grasp pose using similar objects retrieved from shape databases. However, the former faces generalizability challenges when…

Robotics · Computer Science 2023-10-03 Luobin Wang , Runlin Guo , Quan Vuong , Yuzhe Qin , Hao Su , Henrik Christensen

The reconstruction of indoor scenes remains challenging due to the inherent complexity of spatial structures and the prevalence of textureless regions. Recent advancements in 3D Gaussian Splatting have improved novel view synthesis with…

Computer Vision and Pattern Recognition · Computer Science 2024-12-05 Wanting Zhang , Haodong Xiang , Zhichao Liao , Xiansong Lai , Xinghui Li , Long Zeng

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

In this paper, we introduce Point2Mesh, a technique for reconstructing a surface mesh from an input point cloud. Instead of explicitly specifying a prior that encodes the expected shape properties, the prior is defined automatically using…

Graphics · Computer Science 2020-06-16 Rana Hanocka , Gal Metzer , Raja Giryes , Daniel Cohen-Or

In this work, we develop intuitive controls for editing the style of 3D objects. Our framework, Text2Mesh, stylizes a 3D mesh by predicting color and local geometric details which conform to a target text prompt. We consider a disentangled…

Computer Vision and Pattern Recognition · Computer Science 2021-12-07 Oscar Michel , Roi Bar-On , Richard Liu , Sagie Benaim , Rana Hanocka

We study the problem of shape generation in 3D mesh representation from a small number of color images with or without camera poses. While many previous works learn to hallucinate the shape directly from priors, we adopt to further improve…

Computer Vision and Pattern Recognition · Computer Science 2022-04-22 Chao Wen , Yinda Zhang , Chenjie Cao , Zhuwen Li , Xiangyang Xue , Yanwei Fu

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 present Layout-Your-3D, a framework that allows controllable and compositional 3D generation from text prompts. Existing text-to-3D methods often struggle to generate assets with plausible object interactions or require tedious…

Computer Vision and Pattern Recognition · Computer Science 2025-04-08 Junwei Zhou , Xueting Li , Lu Qi , Ming-Hsuan Yang
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