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Generating flexible-view 3D scenes, including 360{\deg} rotation and zooming, from single images is challenging due to a lack of 3D data. To this end, we introduce FlexWorld, a novel framework consisting of two key components: (1) a strong…

Computer Vision and Pattern Recognition · Computer Science 2025-03-20 Luxi Chen , Zihan Zhou , Min Zhao , Yikai Wang , Ge Zhang , Wenhao Huang , Hao Sun , Ji-Rong Wen , Chongxuan Li

3D scene generation seeks to synthesize spatially structured, semantically meaningful, and photorealistic environments for applications such as immersive media, robotics, autonomous driving, and embodied AI. Early methods based on…

Computer Vision and Pattern Recognition · Computer Science 2025-05-09 Beichen Wen , Haozhe Xie , Zhaoxi Chen , Fangzhou Hong , Ziwei Liu

Recovering 3D scenes from sparse views is a challenging task due to its inherent ill-posed problem. Conventional methods have developed specialized solutions (e.g., geometry regularization or feed-forward deterministic model) to mitigate…

Computer Vision and Pattern Recognition · Computer Science 2025-04-04 Hanyang Wang , Fangfu Liu , Jiawei Chi , Yueqi Duan

Humans possess a remarkable ability to mentally explore and replay 3D environments they have previously experienced. Inspired by this mental process, we present EvoWorld: a world model that bridges panoramic video generation with evolving…

Computer Vision and Pattern Recognition · Computer Science 2025-10-02 Jiahao Wang , Luoxin Ye , TaiMing Lu , Junfei Xiao , Jiahan Zhang , Yuxiang Guo , Xijun Liu , Rama Chellappa , Cheng Peng , Alan Yuille , Jieneng Chen

Furnishing and rendering indoor scenes has been a long-standing task for interior design, where artists create a conceptual design for the space, build a 3D model of the space, decorate, and then perform rendering. Although the task is…

Computer Vision and Pattern Recognition · Computer Science 2022-07-26 Hong-Wing Pang , Yingshu Chen , Phuoc-Hieu Le , Binh-Son Hua , Duc Thanh Nguyen , Sai-Kit Yeung

Unbounded 3D world generation is emerging as a foundational task for scene modeling in computer vision, graphics, and robotics. In this work, we present WorldFlow3D, a novel method capable of generating unbounded 3D worlds. Building upon a…

Computer Vision and Pattern Recognition · Computer Science 2026-04-01 Amogh Joshi , Julian Ost , Felix Heide

Single image 3D reconstruction is an important but challenging task that requires extensive knowledge of our natural world. Many existing methods solve this problem by optimizing a neural radiance field under the guidance of 2D diffusion…

Computer Vision and Pattern Recognition · Computer Science 2023-06-30 Minghua Liu , Chao Xu , Haian Jin , Linghao Chen , Mukund Varma T , Zexiang Xu , Hao Su

We introduce Text2Immersion, an elegant method for producing high-quality 3D immersive scenes from text prompts. Our proposed pipeline initiates by progressively generating a Gaussian cloud using pre-trained 2D diffusion and depth…

Computer Vision and Pattern Recognition · Computer Science 2023-12-15 Hao Ouyang , Kathryn Heal , Stephen Lombardi , Tiancheng Sun

Automatically generating a complete 3D scene from a text description, a reference image, or both has significant applications in fields like virtual reality and gaming. However, current methods often generate low-quality textures and…

Computer Vision and Pattern Recognition · Computer Science 2025-04-08 Zhexiao Xiong , Zhang Chen , Zhong Li , Yi Xu , Nathan Jacobs

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

We introduce a novel method for generating 360{\deg} panoramas from text prompts or images. Our approach leverages recent advances in 3D generation by employing multi-view diffusion models to jointly synthesize the six faces of a cubemap.…

Computer Vision and Pattern Recognition · Computer Science 2025-01-29 Nikolai Kalischek , Michael Oechsle , Fabian Manhardt , Philipp Henzler , Konrad Schindler , Federico Tombari

Recent developments in generative models and large-scale datasets have substantially advanced 3D world generation, facilitating a broad range of domains including spatial intelligence, embodied intelligence, and autonomous driving. While…

Computer Vision and Pattern Recognition · Computer Science 2026-05-14 Hanxin Zhu , Cong Wang , Peiyan Tu , Jiayi Luo , Tianyu He , Xin Jin , Zhibo Chen

The growing demand for Embodied AI and VR applications has highlighted the need for synthesizing high-quality 3D indoor scenes from sparse inputs. However, existing approaches struggle to infer massive amounts of missing geometry in large…

Computer Vision and Pattern Recognition · Computer Science 2026-04-15 Dehui Wang , Congsheng Xu , Rong Wei , Yue Shi , Shoufa Chen , Dingxiang Luo , Tianshuo Yang , Xiaokang Yang , Wei Sui , Yusen Qin , Rui Tang , Yao Mu

In this work, we introduce Wonder3D, a novel method for efficiently generating high-fidelity textured meshes from single-view images.Recent methods based on Score Distillation Sampling (SDS) have shown the potential to recover 3D geometry…

Computer Vision and Pattern Recognition · Computer Science 2023-11-10 Xiaoxiao Long , Yuan-Chen Guo , Cheng Lin , Yuan Liu , Zhiyang Dou , Lingjie Liu , Yuexin Ma , Song-Hai Zhang , Marc Habermann , Christian Theobalt , Wenping Wang

A natural approach to generative modeling of videos is to represent them as a composition of moving objects. Recent works model a set of 2D sprites over a slowly-varying background, but without considering the underlying 3D scene that gives…

Computer Vision and Pattern Recognition · Computer Science 2021-03-26 Paul Henderson , Christoph H. Lampert

This paper tackles the problem of generating representations of underwater 3D terrain. Off-the-shelf generative models, trained on Internet-scale data but not on specialized underwater images, exhibit downgraded realism, as images of the…

Graphics · Computer Science 2025-03-11 Tianyi Zhang , Weiming Zhi , Joshua Mangelson , Matthew Johnson-Roberson

We introduce the task of generative panoramic image stitching, which aims to synthesize seamless panoramas that are faithful to the content of multiple reference images containing parallax effects and strong variations in lighting, camera…

Graphics · Computer Science 2025-07-11 Mathieu Tuli , Kaveh Kamali , David B. Lindell

In this paper, we present PanoDreamer, a novel method for producing a coherent 360{\deg} 3D scene from a single input image. Unlike existing methods that generate the scene sequentially, we frame the problem as single-image panorama and…

Computer Vision and Pattern Recognition · Computer Science 2026-01-22 Avinash Paliwal , Xilong Zhou , Andrii Tsarov , Nima Khademi Kalantari

While recent work on text-conditional 3D object generation has shown promising results, the state-of-the-art methods typically require multiple GPU-hours to produce a single sample. This is in stark contrast to state-of-the-art generative…

Computer Vision and Pattern Recognition · Computer Science 2022-12-20 Alex Nichol , Heewoo Jun , Prafulla Dhariwal , Pamela Mishkin , Mark Chen

Panoramic video generation aims to synthesize 360-degree immersive videos, holding significant importance in the fields of VR, world models, and spatial intelligence. Existing works fail to synthesize high-quality panoramic videos due to…

Computer Vision and Pattern Recognition · Computer Science 2025-07-01 Zixun Fang , Kai Zhu , Zhiheng Liu , Yu Liu , Wei Zhai , Yang Cao , Zheng-Jun Zha
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