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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

Spatial intelligence is foundational to AI systems that interact with the physical world, particularly in 3D scene generation and spatial comprehension. Current methodologies for 3D scene generation often rely heavily on predefined…

Computer Vision and Pattern Recognition · Computer Science 2024-12-09 Libin Liu , Shen Chen , Sen Jia , Jingzhe Shi , Zhongyu Jiang , Can Jin , Wu Zongkai , Jenq-Neng Hwang , Lei Li

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

Recent advances in 3D scene generation produce visually appealing output, but current representations hinder artists' workflows that require modifiable 3D textured mesh scenes for visual effects and game development. Despite significant…

Computer Vision and Pattern Recognition · Computer Science 2025-12-22 Tobias Sautter , Jan-Niklas Dihlmann , Hendrik P. A. Lensch

We propose a diffusion-based approach for Text-to-Image (T2I) generation with interactive 3D layout control. Layout control has been widely studied to alleviate the shortcomings of T2I diffusion models in understanding objects' placement…

Computer Vision and Pattern Recognition · Computer Science 2024-08-28 Abdelrahman Eldesokey , Peter Wonka

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

Advances in 3D reconstruction have enabled high-quality 3D capture, but require a user to collect hundreds to thousands of images to create a 3D scene. We present CAT3D, a method for creating anything in 3D by simulating this real-world…

Computer Vision and Pattern Recognition · Computer Science 2024-05-17 Ruiqi Gao , Aleksander Holynski , Philipp Henzler , Arthur Brussee , Ricardo Martin-Brualla , Pratul Srinivasan , Jonathan T. Barron , Ben Poole

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

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

Three-dimensional scene generation is crucial in computer vision, with applications spanning autonomous driving, gaming and the metaverse. Current methods either lack user control or rely on imprecise, non-intuitive conditions. In this…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Yuheng Liu , Xinke Li , Yuning Zhang , Lu Qi , Xin Li , Wenping Wang , Chongshou Li , Xueting Li , Ming-Hsuan Yang

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

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

Metaverse platforms are rapidly evolving to provide immersive spaces for user interaction and content creation. However, the generation of dynamic and interactive 3D objects remains challenging due to the need for advanced 3D modeling and…

Human-Computer Interaction · Computer Science 2025-05-01 Ryutaro Kurai , Takefumi Hiraki , Yuichi Hiroi , Yutaro Hirao , Monica Perusquía-Hernández , Hideaki Uchiyama , Kiyoshi Kiyokawa

Recent advances in 3D representations, such as Neural Radiance Fields and 3D Gaussian Splatting, have greatly improved realistic scene modeling and novel-view synthesis. However, achieving controllable and consistent editing in dynamic 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Kai He , Chin-Hsuan Wu , Igor Gilitschenski

We present DriveGen3D, a novel framework for generating high-quality and highly controllable dynamic 3D driving scenes that addresses critical limitations in existing methodologies. Current approaches to driving scene synthesis either…

Text-driven 3D scene generation techniques have made rapid progress in recent years. Their success is mainly attributed to using existing generative models to iteratively perform image warping and inpainting to generate 3D scenes. However,…

Computer Vision and Pattern Recognition · Computer Science 2024-03-15 Frank Zhang , Yibo Zhang , Quan Zheng , Rui Ma , Wei Hua , Hujun Bao , Weiwei Xu , Changqing Zou

We present InfiniCube, a scalable method for generating unbounded dynamic 3D driving scenes with high fidelity and controllability. Previous methods for scene generation either suffer from limited scales or lack geometric and appearance…

Computer Vision and Pattern Recognition · Computer Science 2025-06-27 Yifan Lu , Xuanchi Ren , Jiawei Yang , Tianchang Shen , Zhangjie Wu , Jun Gao , Yue Wang , Siheng Chen , Mike Chen , Sanja Fidler , Jiahui Huang

In recent years, the demand for 3D content has grown exponentially with the intelligent upgrade of interactive media, extended reality (XR), and Metaverse industries. In order to overcome the limitations of traditional manual modeling…

Graphics · Computer Science 2025-12-23 Xiang Tang , Ruotong Li , Xiaopeng Fan

Authoring 3D scenes is a central task for spatial computing applications. Competing visions for lowering existing barriers are (1) focus on immersive, direct manipulation of 3D content or (2) leverage AI techniques that capture real scenes…

Human-Computer Interaction · Computer Science 2025-12-29 Cyrus Vachha , Yixiao Kang , Zach Dive , Ashwat Chidambaram , Anik Gupta , Eunice Jun , Bjoern Hartmann

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