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Generating 3D scenes from natural language holds great promise for applications in gaming, film, and design. However, existing methods struggle with automation, 3D consistency, and fine-grained control. We present DreamScene, an end-to-end…

Computer Vision and Pattern Recognition · Computer Science 2025-07-30 Haoran Li , Yuli Tian , Kun Lan , Yong Liao , Lin Wang , Pan Hui , Peng Yuan Zhou

3D immersive scene generation is a challenging yet critical task in computer vision and graphics. A desired virtual 3D scene should 1) exhibit omnidirectional view consistency, and 2) allow for free exploration in complex scene hierarchies.…

Computer Vision and Pattern Recognition · Computer Science 2025-02-24 Shuai Yang , Jing Tan , Mengchen Zhang , Tong Wu , Yixuan Li , Gordon Wetzstein , Ziwei Liu , Dahua Lin

In recent years, 3D generation has made great strides in both academia and industry. However, generating 3D scenes from a single RGB image remains a significant challenge, as current approaches often struggle to ensure both object…

Graphics · Computer Science 2026-02-18 Xiang Tang , Ruotong Li , Xiaopeng Fan

3D scene generation is in high demand across various domains, including virtual reality, gaming, and the film industry. Owing to the powerful generative capabilities of text-to-image diffusion models that provide reliable priors, the…

Computer Vision and Pattern Recognition · Computer Science 2024-07-23 Haiyang Zhou , Xinhua Cheng , Wangbo Yu , Yonghong Tian , Li Yuan

3D content creation from a single image is a long-standing yet highly desirable task. Recent advances introduce 2D diffusion priors, yielding reasonable results. However, existing methods are not hyper-realistic enough for post-generation…

Computer Vision and Pattern Recognition · Computer Science 2023-12-08 Tong Wu , Zhibing Li , Shuai Yang , Pan Zhang , Xinggang Pan , Jiaqi Wang , Dahua Lin , Ziwei Liu

The increasing demand for immersive AR/VR applications and spatial intelligence has heightened the need to generate high-quality scene-level and 360${\deg}$ panoramic video. However, most video diffusion models are constrained by limited…

Computer Vision and Pattern Recognition · Computer Science 2025-10-07 Jinxiu Liu , Shaoheng Lin , Yinxiao Li , Ming-Hsuan Yang

Recent advances in text-to-3D creation integrate the potent prior of Diffusion Models from text-to-image generation into 3D domain. Nevertheless, generating 3D scenes with multiple objects remains challenging. Therefore, we present…

Computer Vision and Pattern Recognition · Computer Science 2025-04-03 Yueming Zhao , Xuening Yuan , Hongyu Yang , Di Huang

Generating explorable 3D scenes from a single image is a highly challenging problem in 3D vision. Existing methods struggle to support free exploration, often producing severe geometric distortions and noisy artifacts when the viewpoint…

Computer Vision and Pattern Recognition · Computer Science 2026-03-02 Pengfei Wang , Liyi Chen , Zhiyuan Ma , Yanjun Guo , Guowen Zhang , Lei Zhang

Controllable generative models for images and videos have seen significant success, yet 3D scene generation, especially in unbounded scenarios like autonomous driving, remains underdeveloped. Existing methods lack flexible controllability…

Computer Vision and Pattern Recognition · Computer Science 2025-07-28 Ruiyuan Gao , Kai Chen , Zhihao Li , Lanqing Hong , Zhenguo Li , Qiang Xu

Acquiring detailed 3D scenes typically demands costly equipment, multi-view data, or labor-intensive modeling. Therefore, a lightweight alternative, generating complex 3D scenes from a single top-down image, plays an essential role in…

Computer Vision and Pattern Recognition · Computer Science 2025-10-07 Kaizhi Zheng , Ruijian Zha , Zishuo Xu , Jing Gu , Jie Yang , Xin Eric Wang

Three-dimensional (3D) understanding of objects and scenes play a key role in humans' ability to interact with the world and has been an active area of research in computer vision, graphics, and robotics. Large scale synthetic and…

Computer Vision and Pattern Recognition · Computer Science 2024-12-11 Matthew Wallingford , Anand Bhattad , Aditya Kusupati , Vivek Ramanujan , Matt Deitke , Sham Kakade , Aniruddha Kembhavi , Roozbeh Mottaghi , Wei-Chiu Ma , Ali Farhadi

The synthesis of immersive 3D scenes from text is rapidly maturing, driven by novel video generative models and feed-forward 3D reconstruction, with vast potential in AR/VR and world modeling. While panoramic images have proven effective…

Computer Vision and Pattern Recognition · Computer Science 2026-05-04 Felix Wimbauer , Fabian Manhardt , Michael Oechsle , Nikolai Kalischek , Christian Rupprecht , Daniel Cremers , Federico Tombari

Despite increasingly realistic image quality, recent 3D image generative models often operate on 3D volumes of fixed extent with limited camera motions. We investigate the task of unconditionally synthesizing unbounded nature scenes,…

Computer Vision and Pattern Recognition · Computer Science 2023-03-24 Lucy Chai , Richard Tucker , Zhengqi Li , Phillip Isola , Noah Snavely

Creating immersive and playable 3D worlds from texts or images remains a fundamental challenge in computer vision and graphics. Existing world generation approaches typically fall into two categories: video-based methods that offer rich…

Producing long, coherent video sequences with stable 3D structure remains a major challenge, particularly in streaming scenarios. Motivated by this, we introduce Endless World, a real-time framework for infinite, 3D-consistent video…

Computer Vision and Pattern Recognition · Computer Science 2025-12-16 Ke Zhang , Yiqun Mei , Jiacong Xu , Vishal M. Patel

Explorable 3D world generation from a single image or text prompt forms a cornerstone of spatial intelligence. Recent works utilize video model to achieve wide-scope and generalizable 3D world generation. However, existing approaches often…

Computer Vision and Pattern Recognition · Computer Science 2025-08-12 Zhongqi Yang , Wenhang Ge , Yuqi Li , Jiaqi Chen , Haoyuan Li , Mengyin An , Fei Kang , Hua Xue , Baixin Xu , Yuyang Yin , Eric Li , Yang Liu , Yikai Wang , Hao-Xiang Guo , Yahui Zhou

We present GuidedSceneGen, a text-to-3D generation framework that produces metrically accurate, globally consistent, and semantically interpretable indoor scenes. Unlike prior text-driven methods that often suffer from geometric drift or…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Stefan Ainetter , Thomas Deixelberger , Edoardo A. Dominici , Philipp Drescher , Konstantinos Vardis , Markus Steinberger

Generating a consistent whole-house VR tour from a floorplan and style reference requires both photorealistic panoramas and cross-view spatial coherence. Pure 2D generators produce appealing single panoramas but re-imagine geometry and…

Computer Vision and Pattern Recognition · Computer Science 2026-05-20 Jinrang Jia , Zhenjia Li , Yijiang Hu , Yifeng Shi

Real-world applications like video gaming and virtual reality often demand the ability to model 3D scenes that users can explore along custom camera trajectories. While significant progress has been made in generating 3D objects from text…

Computer Vision and Pattern Recognition · Computer Science 2025-06-05 Tianyu Huang , Wangguandong Zheng , Tengfei Wang , Yuhao Liu , Zhenwei Wang , Junta Wu , Jie Jiang , Hui Li , Rynson W. H. Lau , Wangmeng Zuo , Chunchao Guo

Text-to-3D scene generation holds immense potential for the gaming, film, and architecture sectors. Despite significant progress, existing methods struggle with maintaining high quality, consistency, and editing flexibility. In this paper,…

Computer Vision and Pattern Recognition · Computer Science 2024-07-22 Haoran Li , Haolin Shi , Wenli Zhang , Wenjun Wu , Yong Liao , Lin Wang , Lik-hang Lee , Pengyuan Zhou