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Related papers: PanoWorld-X: Generating Explorable Panoramic World…

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We present PanoWorld, a panoramic video world model that generates geometry-consistent 360$\degree$ video from a single image and a caption. Existing panoramic video methods optimize primarily for visual realism and do not explicitly…

Computer Vision and Pattern Recognition · Computer Science 2026-05-18 Le Jiang , Xiangyu Bai , Bishoy Galoaa , Shayda Moezzi , Caleb James Lee , Tooba Imtiaz , Edmund Yeh , Jennifer Dy , Yanzhi Wang , Sarah Ostadabbas

Panoramic video generation enables immersive 360{\deg} content creation, valuable in applications that demand scene-consistent world exploration. However, existing panoramic video generation models struggle to leverage pre-trained…

Computer Vision and Pattern Recognition · Computer Science 2025-06-26 Yifei Xia , Shuchen Weng , Siqi Yang , Jingqi Liu , Chengxuan Zhu , Minggui Teng , Zijian Jia , Han Jiang , Boxin Shi

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

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

Panoramic video generation has attracted growing attention due to its applications in virtual reality and immersive media. However, existing methods lack explicit motion control and struggle to generate scenes with large and complex…

Computer Vision and Pattern Recognition · Computer Science 2025-12-02 Cheng Zhang , Hanwen Liang , Donny Y. Chen , Qianyi Wu , Konstantinos N. Plataniotis , Camilo Cruz Gambardella , Jianfei Cai

Modeling scenes using video generation models has garnered growing research interest in recent years. However, most existing approaches rely on perspective video models that synthesize only limited observations of a scene, leading to issues…

Computer Vision and Pattern Recognition · Computer Science 2026-04-01 Yuheng Liu , Xin Lin , Xinke Li , Baihan Yang , Chen Wang , Kalyan Sunkavalli , Yannick Hold-Geoffroy , Hao Tan , Kai Zhang , Xiaohui Xie , Zifan Shi , Yiwei Hu

Achieving an immersive experience enabling users to explore virtual environments with six degrees of freedom (6DoF) is essential for various applications such as virtual reality (VR). Wide-baseline panoramas are commonly used in these…

Computer Vision and Pattern Recognition · Computer Science 2023-12-07 Zheng Chen , Yan-Pei Cao , Yuan-Chen Guo , Chen Wang , Ying Shan , Song-Hai Zhang

The rapid advancement of diffusion models holds the promise of revolutionizing the application of VR and AR technologies, which typically require scene-level 4D assets for user experience. Nonetheless, existing diffusion models…

Computer Vision and Pattern Recognition · Computer Science 2025-05-14 Haiyang Zhou , Wangbo Yu , Jiawen Guan , Xinhua Cheng , Yonghong Tian , Li Yuan

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

Diffusion-based methods have achieved remarkable achievements in 2D image or 3D object generation, however, the generation of 3D scenes and even $360^{\circ}$ images remains constrained, due to the limited number of scene datasets, the…

Computer Vision and Pattern Recognition · Computer Science 2024-11-01 Weicai Ye , Chenhao Ji , Zheng Chen , Junyao Gao , Xiaoshui Huang , Song-Hai Zhang , Wanli Ouyang , Tong He , Cairong Zhao , Guofeng Zhang

Controllable spherical panoramic image generation holds substantial applicative potential across a variety of domains.However, it remains a challenging task due to the inherent spherical distortion and geometry characteristics, resulting in…

Computer Vision and Pattern Recognition · Computer Science 2024-03-18 Tao Wu , Xuewei Li , Zhongang Qi , Di Hu , Xintao Wang , Ying Shan , Xi Li

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

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

360{\deg} videos have emerged as a promising medium to represent our dynamic visual world. Compared to the "tunnel vision" of standard cameras, their borderless field of view offers a more complete perspective of our surroundings. While…

Computer Vision and Pattern Recognition · Computer Science 2026-04-24 Rundong Luo , Matthew Wallingford , Ali Farhadi , Noah Snavely , Wei-Chiu Ma

Recently, camera-controlled video generation has seen rapid development, offering more precise control over video generation. However, existing methods predominantly focus on camera control in perspective projection video generation, while…

Computer Vision and Pattern Recognition · Computer Science 2026-04-21 Chenhao Ji , Chaohui Yu , Junyao Gao , Fan Wang , Cairong Zhao

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

Previous works leveraging video models for image-to-3D scene generation tend to suffer from geometric distortions and blurry content. In this paper, we renovate the pipeline of image-to-3D scene generation by unlocking the potential of…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Yuhao Wan , Lijuan Liu , Jingzhi Zhou , Zihan Zhou , Xuying Zhang , Dongbo Zhang , Shaohui Jiao , Qibin Hou , Ming-Ming Cheng

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

Immersive scene generation, notably panorama creation, benefits significantly from the adaptation of large pre-trained text-to-image (T2I) models for multi-view image generation. Due to the high cost of acquiring multi-view images,…

Computer Vision and Pattern Recognition · Computer Science 2024-08-06 Aoming Liu , Zhong Li , Zhang Chen , Nannan Li , Yi Xu , Bryan A. Plummer

Generating multi-camera street-view videos is critical for augmenting autonomous driving datasets, addressing the urgent demand for extensive and varied data. Due to the limitations in diversity and challenges in handling lighting…

Computer Vision and Pattern Recognition · Computer Science 2024-08-09 Jiachen Lu , Ze Huang , Zeyu Yang , Jiahui Zhang , Li Zhang
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