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Related papers: SceneTeller: Language-to-3D Scene Generation

200 papers

Controllable 3D indoor scene synthesis stands at the forefront of technological progress, offering various applications like gaming, film, and augmented/virtual reality. The capability to stylize and de-couple objects within these scenarios…

Computer Vision and Pattern Recognition · Computer Science 2024-01-25 Yunfan Zhang , Hong Huang , Zhiwei Xiong , Zhiqi Shen , Guosheng Lin , Hao Wang , Nicholas Vun

Recent advancements in 3D diffusion-based semantic scene generation have gained attention. However, existing methods rely on unconditional generation and require multiple resampling steps when editing scenes, which significantly limits…

Computer Vision and Pattern Recognition · Computer Science 2024-11-20 Haowen Zheng , Yanyan Liang

The generation of 3D scenes from user-specified conditions offers a promising avenue for alleviating the production burden in 3D applications. Previous studies required significant effort to realize the desired scene, owing to limited…

Computer Vision and Pattern Recognition · Computer Science 2024-11-28 Takayuki Hara , Tatsuya Harada

The rapid progress of large, pretrained models for both visual content generation and 3D reconstruction opens up new possibilities for text-to-3D generation. Intuitively, one could obtain a formidable 3D scene generator if one were able to…

Computer Vision and Pattern Recognition · Computer Science 2026-03-06 Hyojun Go , Dominik Narnhofer , Goutam Bhat , Prune Truong , Federico Tombari , Konrad Schindler

Existing generative approaches for guided image synthesis of multi-object scenes typically rely on 2D controls in the image or text space. As a result, these methods struggle to maintain and respect consistent three-dimensional geometric…

Computer Vision and Pattern Recognition · Computer Science 2025-08-05 Léopold Maillard , Tom Durand , Adrien Ramanana Rahary , Maks Ovsjanikov

Text-to-3D generation is to craft a 3D object according to a natural language description. This can significantly reduce the workload for manually designing 3D models and provide a more natural way of interaction for users. However, this…

Computer Vision and Pattern Recognition · Computer Science 2023-09-27 Han Yi , Zhedong Zheng , Xiangyu Xu , Tat-seng Chua

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

Learning descriptive 3D features is crucial for understanding 3D scenes with diverse objects and complex structures. However, it is usually unknown whether important geometric attributes and scene context obtain enough emphasis in an…

Computer Vision and Pattern Recognition · Computer Science 2022-12-13 Junbo Zhang , Guofan Fan , Guanghan Wang , Zhengyuan Su , Kaisheng Ma , Li Yi

The connection between our 3D surroundings and the descriptive language that characterizes them would be well-suited for localizing and generating human motion in context but for one problem. The complexity introduced by multiple modalities…

Computer Vision and Pattern Recognition · Computer Science 2024-05-30 Zoltán Á. Milacski , Koichiro Niinuma , Ryosuke Kawamura , Fernando de la Torre , László A. Jeni

Scene image editing is crucial for entertainment, photography, and advertising design. Existing methods solely focus on either 2D individual object or 3D global scene editing. This results in a lack of a unified approach to effectively…

Computer Vision and Pattern Recognition · Computer Science 2024-05-29 Qihang Zhang , Yinghao Xu , Chaoyang Wang , Hsin-Ying Lee , Gordon Wetzstein , Bolei Zhou , Ceyuan Yang

Diffusion-based methods have achieved prominent success in generating 2D media. However, accomplishing similar proficiencies for scene-level mesh texturing in 3D spatial applications, e.g., XR/VR, remains constrained, primarily due to the…

Computer Vision and Pattern Recognition · Computer Science 2023-10-23 Bangbang Yang , Wenqi Dong , Lin Ma , Wenbo Hu , Xiao Liu , Zhaopeng Cui , Yuewen Ma

Recent advances in large language models (LLMs) enable compelling story generation, but connecting narrative text to playable visual environments remains an open challenge in procedural content generation (PCG). We present a lightweight…

Graphics · Computer Science 2026-01-05 Yi-Chun Chen , Arnav Jhala

In this paper, we propose Extend3D, a training-free pipeline for 3D scene generation from a single image, built upon an object-centric 3D generative model. To overcome the limitations of fixed-size latent spaces in object-centric models for…

Computer Vision and Pattern Recognition · Computer Science 2026-04-01 Seungwoo Yoon , Jinmo Kim , Jaesik Park

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

In this work, we explore the challenging task of generating 3D shapes from text. Beyond the existing works, we propose a new approach for text-guided 3D shape generation, capable of producing high-fidelity shapes with colors that match the…

Computer Vision and Pattern Recognition · Computer Science 2022-03-29 Zhengzhe Liu , Yi Wang , Xiaojuan Qi , Chi-Wing Fu

We consider the task of generating designs directly from natural language descriptions, and consider floor plan generation as the initial research area. Language conditional generative models have recently been very successful in generating…

Computation and Language · Computer Science 2023-11-28 Sicong Leng , Yang Zhou , Mohammed Haroon Dupty , Wee Sun Lee , Sam Conrad Joyce , Wei Lu

Text-to-3D generation has achieved remarkable success via large-scale text-to-image diffusion models. Nevertheless, there is no paradigm for scaling up the methodology to urban scale. Urban scenes, characterized by numerous elements,…

Computer Vision and Pattern Recognition · Computer Science 2024-04-11 Fan Lu , Kwan-Yee Lin , Yan Xu , Hongsheng Li , Guang Chen , Changjun Jiang

As Artificial Intelligence Generated Content (AIGC) advances, a variety of methods have been developed to generate text, images, videos, and 3D objects from single or multimodal inputs, contributing efforts to emulate human-like cognitive…

Computer Vision and Pattern Recognition · Computer Science 2024-08-21 Yiying Yang , Fukun Yin , Jiayuan Fan , Xin Chen , Wanzhang Li , Gang Yu

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…

We pose 3D scene-understanding as a problem of parsing in a grammar. A grammar helps us capture the compositional structure of real-word objects, e.g., a chair is composed of a seat, a back-rest and some legs. Having multiple rules for an…

Computer Vision and Pattern Recognition · Computer Science 2012-11-09 Abhishek Anand , Sherwin Li
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